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The dynamical formation of binary black holes (BBHs) in globular clusters (GCs) may contribute significantly to the observed gravitational wave (GW) merger rate. Furthermore, LISA may detect many BBH sources from GCs at mHz frequencies, enabling the characterization of such systems within the Milky Way and nearby Universe. In this work, we use Monte Carlo N-body simulations to construct a realistic sample of Galactic clusters, thus estimating the population, detectability, and parameter measurement accuracy of BBHs hosted within them. In particular, we show that the GW signal from $0.7\pm 0.7$, $2.0\pm 1.7$, $3.6\pm 2.3$, $13.4\pm 4.7$ BBHs in Milky Way GCs can exceed the signal-to-noise ratio threshold of $\rm SNR =30$, 5, 3, and 1 for a 10-year LISA observation, with $\sim 50\%$ of detectable sources exhibiting high eccentricities ($e\gtrsim0.9$). Moreover, the Fisher matrix and Bayesian analyses of the GW signals indicate these systems typically feature highly-resolved orbital frequencies ($\delta f_{\rm orb}/ f_{\rm orb} \sim 10^{-7}-10^{-5}$) and eccentricities ($\delta e/ e \sim 10^{-3}-0.1$), as well as a measurable total mass when SNR exceeds $\sim20$. Notably, BBHs with $\rm SNR\gtrsim 20$ can be confidently localized to specific GCs within the Milky Way, with an angular resolution of $\sim 10-100$ arc minutes. The detection and localization of even a single BBH in a Galactic GC would allow accurate tracking of its long-term orbital evolution, enable a direct test of the role of GCs in BBH formation, and provide a unique probe into the evolutionary history of Galactic clusters., Comment: 12+4 pages, 5 figures. Comments are welcome

Merging binary black holes (BBHs) formed dynamically in dense star clusters are expected to have uncorrelated spin--orbit orientations since they are assembled through many random interactions. However, measured effective spins in BBHs detected by LIGO/Virgo/KAGRA hint at additional physical processes that may introduce anisotropy. Here we address this question by exploring the impact of stellar collisions, and accretion of collision debris, on the spin--orbit alignment in merging BBHs formed in dense star clusters. Through hydrodynamic simulations, we study the regime where the disruption of a massive star by a BBH causes the stellar debris to form individual accretion disks bound to each black hole. We show that these disks, which are randomly oriented relative to the binary orbital plane after the initial disruption of the star, can be reoriented by strong tidal torques in the binary near pericenter passages. Following accretion by the BHs on longer timescales, BBHs with small but preferentially positive effective spin parameters ($\chi_{\rm eff} \lesssim 0.2$) are formed. Our results indicate that BBH collisions in young massive star clusters could contribute to the observed trend toward small positive $\chi_{\rm eff}$, and we suggest that the standard assumption often made that dynamically assembled BBHs should have isotropically distributed BH spins is not always justified., Comment: 13 pages, 6 figures, V1

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field.

Exploiting quantum effects of mechanical motion, such as backaction evading measurements or squeezing, requires preparation of the oscillator in a high-purity state. The largest state purities in optomechanics to date have relied on cryogenic cooling, combined with coupling to electromagnetic resonators driven with a coherent radiation field. In this work, we cool the mega-hertz-frequency librational mode of an optically levitated silica nanoparticle from room temperature to its quantum ground state. Cooling is realized by coherent scattering into a Fabry-Perot cavity. We use sideband thermometry to infer a phonon population of 0.04 quanta under optimal conditions, corresponding to a state purity of 92%. The purity reached by our room-temperature experiment exceeds the performance offered by mechanically clamped oscillators in a cryogenic environment. Our work establishes a platform for high-purity quantum optomechanics at room temperature.

By single crystal diffraction we characterize the chemo-structural disorder introduced by Zn-Cu site mixing in the kagom\'e spin $S$-1/2 systems herbertsmithite ZnCu$_3$(OH)$_6$Cl$_2$ and YCu$_3$(OH)$_{6}$Br$_{2}$[Br$_x$(OH)$_{1-x}$]. For an untwinned single crystal of herbertsmithite of composition Zn$_{0.95(1)}$Cu$_{2.99(3)}$O$_{5.9(1)}$H$_{5.8(1)}$Cl$_2$ we find substitution by Cu of the Zn atoms in the layers separating the kagom\'e layers as well as substantial Zn substitution for Cu in the kagom\'e layers. In YCu$_3$(OH)$_{6}$Br$_{2}$[Br$_x$(OH)$_{1-x}$] site mixing disorder is present for intermediate $x$. Analogous to the Cl homologous system in crystals with $x = 1/3$ disorder is absent and a low-temperature structural transition emerges driven by strong magneto-phonon coupling as a release of frustration. Apart from this structural anomaly we find the physical properties of these crystals unchanged compared to intermediate $x$ and closely resembling the Cl homologue where long-range magnetic order was observed.

The cylindrical algebraic covering method was originally proposed to decide the satisfiability of a set of non-linear real arithmetic constraints. We reformulate and extend the cylindrical algebraic covering method to allow for checking the truth of arbitrary non-linear arithmetic formulas, adding support for both quantifiers and Boolean structure. Furthermore, we also propose a variant to perform quantifier elimination on such formulas. After introducing the algorithm, we elaborate on various extensions, optimizations and heuristics. Finally, we present an experimental evaluation of our implementation and provide a comparison with state-of-the-art SMT solvers and quantifier elimination tools.

We generalise the classical Bass-Heller-Swan decomposition for the K-theory of (twisted) Laurent algebras to a splitting for general localising invariants of certain categories of twisted automorphisms. As an application, we obtain splitting formulas for Waldhausen's A-theory of mapping tori and for the K-theory of certain tensor algebras. We identify the Nil-terms appearing in this splitting in two ways. Firstly, as the reduced K-theory of twisted endomorphisms. Secondly, as the reduced K-theory of twisted nilpotent endomorphisms. Finally, we generalise classical vanishing results for Nil-terms of regular rings to our setting., Comment: 30 pages. Comments welcome!

Fluid transport across nanometric channels induced by electric, pressure and concentration gradients is ubiquitous in biological systems and fosters various applications. In this context, computer simulation setups with well-defined open-boundary equilibrium starting states are essential in understanding and assisting experimental studies. However, open-boundary computational methods are scarce and typically do not satisfy all the equilibrium conditions imposed by reality. Namely, in the absence of external gradients, 1) the system of interest (SoI) must be at thermodynamic and chemical equilibrium with an infinite reservoir of particles, 2) the fluctuations of the SoI in equilibrium should sample the grand canonical ensemble, 3) the local solvation thermodynamics, which is extremely sensitive to finite-size effects due to solvent depletion, should be correctly described. This point is particularly relevant for out-of-equilibrium systems. Finally, 4) the method should be robust enough to deal with phase transitions and coexistence conditions in the SoI. In this study, we demonstrate with prototypical liquid systems embedded into a reservoir of ideal gas particles that the adaptive resolution simulation (AdResS) method, coupled with particle insertion/deletion steps, satisfies all these requirements. Therefore, this AdResS setup is suitable for performing equilibrium and non-equilibrium simulations of open systems.

Tidal disruption events (TDEs) are an important way to probe the properties of stellar populations surrounding supermassive black holes. Observed spectra of several TDEs, such as ASASSN-14li, show high nitrogen to carbon abundance ratios, leading to questions about their progenitors. Disrupting an intermediate- or high-mass star that has undergone CNO processing, increasing the nitrogen in its core, could lead to an enhanced nitrogen TDE. Galactic nuclei present a conducive environment for high-velocity stellar collisions that can lead to high mass loss, stripping the carbon- and hydrogen-rich envelopes of the stars and leaving behind the enhanced nitrogen cores. TDEs of these stripped stars may therefore exhibit even more extreme nitrogen enhancement. Using the smoothed particle hydrodynamics code StarSmasher, we provide a parameter space study of high-velocity stellar collisions involving intermediate-mass stars, analyzing the composition of the collision products. We conclude that high-velocity stellar collisions can form products that have abundance ratios similar to those observed in the motivating TDEs. Furthermore, we show that stars that have not experienced high CNO processing can yield low-mass collision products that retain even higher nitrogen to carbon abundance ratios. We analytically estimate the mass fallback for a typical TDE of several collision products to demonstrate consistency between our models and TDE observations. Lastly, we discuss how the extended collision products, with high central to average density ratios, can be related to repeated partial TDEs like ASASSN-14ko and G objects in the Galactic Center., Comment: 26 pages, 10 figures, 3 tables, submitted to ApJ

Dynamical interactions in dense star clusters could significantly influence the properties of black holes, leaving imprints on their gravitational-wave signatures. While previous studies have mostly focused on repeated black hole mergers for spin and mass growth, this work examines the impact of physical collisions and close encounters between black holes and (non-compact) stars. Using Monte Carlo N-body models of dense star clusters, we find that a large fraction of black holes retained upon formation undergo collisions with stars. Within our explored cluster models, the proportion of binary black hole mergers affected by stellar collisions ranges from $10\%$ to $60\%$. If all stellar-mass black holes are initially non-spinning, we find that up to $40\%$ of merging binary black holes may have components with dimensionless spin parameter $\chi\gtrsim 0.2$ because of prior stellar collisions, while typically about $10\%$ have spins near $\chi = 0.7$ from prior black hole mergers. We demonstrate that young star clusters are especially important environments as they can produce collisions of black holes with very massive stars, allowing significant spin up of the black holes through accretion. Our predictions for black hole spin distributions from these stellar collisions highlight their sensitivity to accretion efficiency, underscoring the need for detailed hydrodynamic calculations to better understand the accretion physics following these interactions., Comment: 16 pages, 8 figures, 2 tables. Accepted to ApJ

To search for a conceptual picture describing the magnetization plateau phenomenon, we surveyed the crystal structures and the spin lattices of those magnets exhibiting plateaus in their magnetization vs. magnetic field curves by probing the three questions: (a) why only certain magnets exhibit magnetization plateaus, (b) why there occur several different types of magnetization plateaus, and (c) what controls the widths of magnetization plateaus. We show that the answers to these questions lie in how the magnets under field absorb Zeeman energy hence changing their magnetic structures. The magnetic structure of a magnet insulator is commonly described in terms of its spin lattice, which requires the determination of the spin exchanges nonnegligible strengths between the magnetic ions. Our work strongly suggests that a magnet under magnetic field partitions its spin lattice into antiferromagnetic (AFM) or ferrimagnetic fragments by breaking its weak magnetic bonds. Our supposition of the field-induced partitioning of spin lattice into magnetic fragments is supported by the anisotropic magnetization plateaus of Ising magnets and by the highly anisotropic width of the 1/3-magnetization plateau in azurite. The answers to the three questions (a) - (c) emerge naturally by analyzing how these fragments are formed under magnetic field., Comment: A survey of the magnetization plateau phenomenon; 128 pages including the Supporting Information

Wide, highly eccentric ($e>0.9$) compact binaries can naturally arise as progenitors of gravitational wave (GW) mergers. These systems are expected to have a significant population in the mHz band (e.g., $\sim 3-45$ detectable stellar-mass binary black holes with $e>0.9$ in the Milky Way), with their GW signals characterized by "repeated bursts" emitted upon each pericenter passage. In this study, we show that the detection of mHz GW signals from highly eccentric stellar mass binaries in the local universe can strongly constrain their orbital parameters. Specifically, it can achieve a relative measurement error of $\sim 10^{-6}$ for orbital frequency and $\sim 1\%$ for eccentricity (as $1-e$) in most of the detectable cases. On the other hand, the binary's mass ratio, distance, and intrinsic orbital orientation may be less precisely determined due to degeneracies in the GW waveform. We also perform mock LISA data analysis to evaluate the realistic detectability of highly eccentric compact binaries. Our results show that highly eccentric systems could be efficiently identified when multiple GW sources and stationary Gaussian instrumental noise are present in the detector output. This work highlights the potential of extracting the signal of "bursting'' LISA sources to provide valuable insights into their orbital evolution, surrounding environment, and formation channels., Comment: 17+9 pages, 6+3 figures. Accepted by PRD

Alongside the population of several hundred radio millisecond pulsars currently known in Milky Way globular clusters, a subset of six slowly spinning pulsars (spin periods $0.3-4\,$s) are also observed. With inferred magnetic fields $\gtrsim 10^{11}\,$G and characteristic ages $\lesssim10^8\,$yr, explaining the formation of these apparently young pulsars in old stellar populations poses a major challenge. One popular explanation is that these objects are not actually young but instead have been partially spun up via accretion from a binary companion. In this scenario, accretion in a typical low-mass X-ray binary is interrupted by a dynamical encounter with a neighboring object in the cluster. Instead of complete spin up to millisecond spin periods, the accretion is halted prematurely, leaving behind a ''partially recycled'' neutron star. In this Letter, we use a combination of analytic arguments motivated by low-mass X-ray binary evolution and $N$-body simulations to show that this partial-recycling mechanism is not viable. Realistic globular clusters are not sufficiently dense to interrupt mass transfer on the short timescales required to achieve such slow spin periods. We argue that collapse of massive white dwarfs and/or neutron star collisions are more promising ways to form slow pulsars in old globular clusters., Comment: 9 pages, 2 figures. Accepted for publication in ApJL

We study the Volterra Volterra Cox-Ingersoll-Ross process on $\mathbb{R}_+$ and its stationary version. Based on a fine asymptotic analysis of the corresponding Volterra Riccati equation combined with the affine transformation formula, we first show that the finite-dimensional distributions of this process are asymptotically independent. Afterwards, we prove a law-of-large numbers in $L^p$(\Omega)$ with $p \geq 2$ and show that the stationary process is ergodic. As an application, we prove the consistency of the method of moments and study the maximum-likelihood estimation for continuous and discrete high-frequency observations., Comment: arXiv admin note: substantial text overlap with arXiv:2404.05554

We consider slow-roll inflation in the context of a modified Brans-Dicke dilaton gravity. From a two self-interacting potentials $V(\phi)$, we reproduce a Starobinsky-like potential and, commonly in syperstring models, an exponential tail potential $V(\phi)\sim(1-e^{\alpha_0\phi})$, with $\alpha_0$ being a constant coefficient related to the Brans-Dicke parameter $\omega$. Using the observational bounds on the spectral index $n_s$ and tensor-to-scalar ratio $r$ imposed by Planck-CMB baseline data and the BICEP2/Keck collaboration with combination with Planck 2018 and the Baryonic Acoustic Oscillations(BAO), we obtain for both models a good agreement with current observations with $n_s = 0.960 - 0.972$ and $r<0.02$. In addition, the resulting large values of $\omega$ suggests a possible linkage of the inflationary regime and today's solar system bounds., Comment: revised version, updated references

In this companion article to [HKK24], we apply the theory of equivariant Poincar\'e duality developed there in the special case of cyclic groups $C_p$ of prime order to remove, in a special case, a technical condition given by Davis--L\"uck [DL24] in their work on the Nielsen realisation problem for aspherical manifolds. Along the way, we will also give a complete characterisation of $C_p$--Poincar\'e spaces as well as introduce a genuine equivariant refinement of the classical notion of virtual Poincar\'e duality groups which might be of independent interest., Comment: 30 pages. Comments welcome!

The widespread application of Artificial Intelligence (AI) techniques has significantly influenced the development of new therapeutic agents. These computational methods can be used to design and predict the properties of generated molecules. Multi-target Drug Discovery (MTDD) is an emerging paradigm for discovering drugs against complex disorders that do not respond well to more traditional target-specific treatments, such as central nervous system, immune system, and cardiovascular diseases. Still, there is yet to be an established benchmark suite for assessing the effectiveness of AI tools for designing multi-target compounds. Standardized benchmarks allow for comparing existing techniques and promote rapid research progress. Hence, this work proposes an evaluation framework for molecule generation techniques in MTDD scenarios, considering brain diseases as a case study. Our methodology involves using large language models to select the appropriate molecular targets, gathering and preprocessing the bioassay datasets, training quantitative structure-activity relationship models to predict target modulation, and assessing other essential drug-likeness properties for implementing the benchmarks. Additionally, this work will assess the performance of four deep generative models and evolutionary algorithms over our benchmark suite. In our findings, both evolutionary algorithms and generative models can achieve competitive results across the proposed benchmarks., Comment: 8 pages, 1 figure, published in 2024 IEEE Congress on Evolutionary Computation (CEC)

A kinetic theory for moderately dense gases of inelastic and rough spherical molecules is developed from the Enskog equation where a macroscopic state is characterized by 29 scalar fields which correspond to the moments of the distribution function: mass density, hydrodynamic velocity, pressure tensor, absolute temperature, translational and rotational heat fluxes, hydrodynamic angular velocity and angular velocity flux. The balance equations for the 29 scalar fields are obtained from a transfer equation derived from the Enskog equation where the kinetic and potential parts of the new moments of the distribution function and production terms are calculated from Grad's distribution function for the basic fields. The transition from the 29 field theory to an eight field theory -- with mass density, hydrodynamic velocity, absolute temperature and hydrodynamic angular velocity -- leads to the determination of the transport coefficients of the Navier-Stokes and Fourier laws. The transport coefficients are functions of the normal and tangential restitution coefficients and of the local equilibrium radial distribution function. The transport coefficients in the limiting case of elastic rough spheres is also determined., Comment: 20 pages

The existence of compact stellar remnants in the mass range $2-5\,M_{\odot}$ has long been debated. This so-called lower mass gap was initially suggested by the lack of low-mass X-ray binary observations with accretors about $2-5\,M_{\odot}$, but it has recently been called into question following newer observations, including a lower-mass-gap candidate with a millisecond pulsar companion in the dense globular cluster NGC 1851. Here we model NGC 1851 with a grid of similar dense star clusters utilizing the state-of-the-art Monte Carlo $N$-body code \texttt{CMC}, and we specifically study the formation of lower-mass-gap black holes. We demonstrate that both massive star evolution and dynamical interactions can contribute to forming lower-mass-gap black holes. In general, the collapse of massive remnants formed through mergers of neutron stars or massive white dwarfs produces the largest number of lower-mass-gap black holes among all formation channels. However, in more massive clusters, supernova core collapse can contribute comparable numbers. Our NGC 1851-like models can reproduce millisecond pulsar -- lower-mass-gap black hole binaries similar to the observed system. Additionally, the lower-mass-gap black holes can also become components of dynamically assembled binaries, and some will be in merging black hole - neutron star systems similar to the recently detected gravitational wave source GW230529. However, the corresponding merger rate is probably $\lesssim 1~{\rm Gpc^{-3}\,yr^{-1}}$., Comment: 18 pages, 7 figures, 3 tables. Published at ApJ

This paper explores artificial intelligence (AI) methods for the approximate compiling of unitaries, focusing on the use of fixed two-qubit gates and arbitrary single-qubit rotations typical in superconducting hardware. Our approach involves three main stages: identifying an initial template that approximates the target unitary, predicting initial parameters for this template, and refining these parameters to maximize the fidelity of the circuit. We propose AI-driven approaches for the first two stages, with a deep learning model that suggests initial templates and an autoencoder-like model that suggests parameter values, which are refined through gradient descent to achieve the desired fidelity. We demonstrate the method on 2 and 3-qubit unitaries, showcasing promising improvements over exhaustive search and random parameter initialization. The results highlight the potential of AI to enhance the transpiling process, supporting more efficient quantum computations on current and future quantum hardware.

The perovskite oxide EuTiO3 (ETO) has attracted increased scientific interest due to its potential multiferroic properties and magnetic activity above and below its structural phase transition at TS=282K. Various experiments have indirectly evidenced that this transition is neither a cubic tetragonal nor the only one occurring in ETO. Here, we show new results demonstrating two further instabilities below TS based on lattice dynamics and spin-phonon interactions combined with a Landau free energy model with coupled order parameters. The new transition temperatures perfectly agree with available experimental data where further instabilities have been anticipated., Comment: 14 pages, 5 figures

The superposition of frequency-shifted Laguerre-Gauss modes can produce a rotating saddle-like intensity profile. When spinning fast enough, the optical forces produced by this structured light saddle generate a dynamically stable equilibrium point capable of trapping nanoparticles in a high vacuum, akin to a Paul trap but with its unique characteristics. We analyze the stability conditions and center-of-mass motion, dynamics and cooling of a nanoparticle levitated in the optical saddle trap. We expect the optical saddle to find applications in levitated optomechanics experiments requiring fast parametric modulation and inverted squeezing potential landscapes.

Competing interactions in low-dimensional materials can produce nearly degenerate electronic and structural phases. We investigate the staircase of structural phase transitions in layered IrTe$_2$ for which a number of potential transition mechanisms have been postulated. The spatial coexistence of multiple phases on the micron scale has prevented a detailed analysis of the electronic structure. By exploiting micro-ARPES obtained with synchrotron radiation we extract the electronic structure of the multiple structural phases in IrTe$_2$ in order to address the mechanism underlying the phase transitions. We find direct evidence of lowered energy states that appear in the low-temperature phases, states previously predicted by \textit{ab initio} calculations and extended here. Our results validate a proposed scenario of bonding and anti-bonding states as the driver of the phase transitions., Comment: None

We report the discovery of a high velocity, very low-mass star or brown dwarf whose kinematics suggest it is unbound to the Milky Way. CWISE J124909.08+362116.0 was identified by citizen scientists in the Backyard Worlds: Planet 9 program as a high proper motion ($\mu$ $=$ 0''9/yr) faint red source. Moderate resolution spectroscopy with Keck/NIRES reveals it to be a metal-poor early L subdwarf with a large radial velocity ($-$103$\pm$10 km/s), and its estimated distance of 125$\pm$8 pc yields a speed of 456$\pm$27 km/s in the Galactic rest frame, near the local escape velocity for the Milky Way. We explore several potential scenarios for the origin of this source, including ejection from the Galactic center $\gtrsim$3 Gyr in the past, survival as the mass donor companion to an exploded white dwarf. acceleration through a three-body interaction with a black hole binary in a globular cluster, and accretion from a Milky Way satellite system. CWISE J1249+3621 is the first hypervelocity very low mass star or brown dwarf to be found, and the nearest of all such systems. It may represent a broader population of very high velocity, low-mass objects that have undergone extreme accelerations., Comment: 17 pages, 3 figures, accepted for publication in Astrophysical Journal Letters

Quantum programs are typically developed using quantum Software Development Kits (SDKs). The rapid advancement of quantum computing necessitates new tools to streamline this development process, and one such tool could be Generative Artificial intelligence (GenAI). In this study, we introduce and use the Qiskit HumanEval dataset, a hand-curated collection of tasks designed to benchmark the ability of Large Language Models (LLMs) to produce quantum code using Qiskit - a quantum SDK. This dataset consists of more than 100 quantum computing tasks, each accompanied by a prompt, a canonical solution, a comprehensive test case, and a difficulty scale to evaluate the correctness of the generated solutions. We systematically assess the performance of a set of LLMs against the Qiskit HumanEval dataset's tasks and focus on the models ability in producing executable quantum code. Our findings not only demonstrate the feasibility of using LLMs for generating quantum code but also establish a new benchmark for ongoing advancements in the field and encourage further exploration and development of GenAI-driven tools for quantum code generation.

Code Large Language Models (Code LLMs) have emerged as powerful tools, revolutionizing the software development landscape by automating the coding process and reducing time and effort required to build applications. This paper focuses on training Code LLMs to specialize in the field of quantum computing. We begin by discussing the unique needs of quantum computing programming, which differ significantly from classical programming approaches or languages. A Code LLM specializing in quantum computing requires a foundational understanding of quantum computing and quantum information theory. However, the scarcity of available quantum code examples and the rapidly evolving field, which necessitates continuous dataset updates, present significant challenges. Moreover, we discuss our work on training Code LLMs to produce high-quality quantum code using the Qiskit library. This work includes an examination of the various aspects of the LLMs used for training and the specific training conditions, as well as the results obtained with our current models. To evaluate our models, we have developed a custom benchmark, similar to HumanEval, which includes a set of tests specifically designed for the field of quantum computing programming using Qiskit. Our findings indicate that our model outperforms existing state-of-the-art models in quantum computing tasks. We also provide examples of code suggestions, comparing our model to other relevant code LLMs. Finally, we introduce a discussion on the potential benefits of Code LLMs for quantum computing computational scientists, researchers, and practitioners. We also explore various features and future work that could be relevant in this context.

The origins and mergers of supermassive black holes (BHs) remain a mystery. We describe a scenario from a novel multi-physics simulation featuring rapid ($\lesssim 1\,$Myr) hyper-Eddington gas capture by a $\sim 1000\,{\rm M}_{\odot}$ ``seed'' BH up to supermassive ($\gtrsim 10^{6}\,M_{\odot}$) masses, in a massive, dense molecular cloud complex typical of high-redshift starbursts. Due to the high cloud density, stellar feedback is inefficient and most of the gas turns into stars in star clusters which rapidly merge hierarchically, creating deep potential wells. Relatively low-mass BH seeds at random positions can be ``captured'' by merging sub-clusters and migrate to the center in $\sim1$ free-fall time (vastly faster than dynamical friction). This also efficiently produces a paired BH binary with $\sim 0.1$\,pc separation. The centrally-concentrated stellar density profile (akin to a ``proto-bulge'') allows the cluster as a whole to capture and retain gas and build up a large (pc-scale) circum-binary accretion disk with gas coherently funnelled to the central BH (even when the BH radius of influence is small). The disk is ``hyper-magnetized'' and ``flux-frozen'': dominated by a toroidal magnetic field with plasma $\beta \sim 10^{-3}$, with the fields amplified by flux-freezing. This drives hyper-Eddington inflow rates $\gtrsim 1\,\rm M_\odot yr^{-1}$, which also drive the two BHs to nearly-equal masses. The late-stage system appears remarkably similar to recently-observed high-redshift ``little red dots.'' This scenario can provide an explanation for rapid SMBH formation, growth and mergers in high-redshift galaxies., Comment: 9 pages, 5 figures, final version matching the publication

In this article, we introduce and develop the notion of parametrised Poincar\'{e} duality in the formalism of parametrised higher category theory by Martini-Wolf, in part generalising Cnossen's theory of twisted ambidexterity to the nonpresentable setting. We prove several basechange results, allowing us to move between different coefficient categories and ambient topoi. We then specialise the general framework to yield a good theory of equivariant Poincar\'{e} duality spaces for compact Lie groups and apply our basechange results to obtain a suite of isotropy separation methods. Finally, we employ this theory to perform various categorical Smith-theoretic manoeuvres to prove, among other things, a generalisation of a theorem of Atiyah-Bott and Conner-Floyd on group actions with single fixed points., Comment: 97 pages. Comments welcome!

This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By employing RL, we achieve near-optimal synthesis of Linear Function, Clifford, and Permutation circuits, up to 9, 11 and 65 qubits respectively, while being compatible with native device instruction sets and connectivity constraints, and orders of magnitude faster than optimization methods such as SAT solvers. We also achieve significant reductions in two-qubit gate depth and count for circuit routing up to 133 qubits with respect to other routing heuristics such as SABRE. We find the method to be efficient enough to be useful in practice in typical quantum transpiling pipelines. Our results set the stage for further AI-powered enhancements of quantum computing workflows.