Search

We develop a new semi-analytic framework of Population (Pop) III and subsequent galaxy formation designed to run on dark matter halo merger trees. In our framework, we consider the effect of the Lyman-Werner flux from Pop III and II stars and the dark matter baryon streaming velocity on the critical minihalo mass for the Pop III formation. Our model incorporates the Lyman-Werner feedback in a self-consistent way, therefore, the spatial variation of Lyman-Werner feedback naturally emerges. The Pop III mass depends on the properties of a minihalo as reproducing radiative hydrodynamical simulation results. We perform statistical studies of Pop III stars by applying this framework to high-resolution cosmological N-body simulations with a maximum box size of 16 Mpc/h and enough mass resolution to resolve Pop III-forming minihalos. A top-heavy initial mass function emerges and two peaks corresponding to the H$_2$ ($20 \lesssim z \lesssim 25$) and atomic cooling halos ($z \lesssim 15$) exist in the distribution. Supermassive stars can be formed in the atomic cooling halos, and the fractions of such supermassive stars increase with the value of streaming velocity. At least an 8 Mpc/h simulation box and the self-consistent model for the Lyman-Werner feedback are necessary to correctly model the Pop III formation in the atomic cooling halos. Our model predicts one supermassive star per halo with several $10^9$ Msun at z=7.5, which is enough to reproduce a high redshift quasar., Comment: 18 pages, 10 figures, submitted to ApJ

Recent high-resolution observations have enabled detailed investigations of the circumstellar environments around Class 0/I protostars. Several studies have reported that the infall velocity of the envelope is a few times smaller than the free-fall velocity inferred from protostellar masses estimated via the observed rotational velocity of their Keplerian disks. To explore the physical origins of the slow infall, we perform a set of three-dimensional non-ideal magnetohydrodynamic simulations of the star formation process, extending to $10^5$ yr after protostar formation. Our simulations show that the infall velocity decreases markedly at the outer edge of the pseudo-disk (at radii of $\sim \! 100-1000$ au) and is much slower than the expected free-fall velocity. The degree of this reduction depends on (1) the initial magnetic field strength, (2) the alignment between the initial field and the rotation axis, and (3) the evolutionary stage of the system. Across our parameter space, the ratio of the infall velocity to the free-fall velocity is as small as $0.2-0.5$, which is consistent with the observations. We further examine the reliability of protostellar mass estimates derived from infall and rotational velocities. While the mass derived from disk rotation closely matches the true value, deviation by a factor of $0.3-2$ is found for the estimates using the infall velocity; it is underestimated due to slow infall, but could also be overestimated due to the contribution of disk mass. These findings underscore the critical role of magnetic fields in shaping star formation dynamics and highlight the uncertainties associated with protostellar mass estimates., Comment: 13 pages, 12 figures, 1 table, submitted to ApJ

The formation and mass distribution of the first stars depend on various environmental factors in the early universe. We compare 120 cosmological hydrodynamical simulations to explore how the baryonic streaming velocity (SV) relative to dark matter affects the formation of the first stars. We vary SV from zero to three times its cosmic root-mean-square value, $v_{\rm SV}/\sigma_{\rm SV}=0-3$, and identify 20 representative halos from cosmological simulations. For each model, we follow the evolution of a primordial star-forming cloud from the first appearance of a dense core (with gas density > $10^{6}\,{\rm cm^{-3}}$) until 2 Myr later. In each model, higher SV systematically delays the formation of primordial clouds, formed inside more massive halos ($10^{5}-10^{7}\,{\rm M}_\odot$), and promotes cloud-scale fragmentation and multiple-core formation. The number and total mass of dense cores increase with increasing SV. More than half of models with $v_{\rm SV}/\sigma_{\rm SV} \ge 1.5$ form three or more dense cores in a single halo. In extreme cases, up to 25 cores form at once, which leaves a massive first star cluster. On the other hand, models with $v_{\rm SV}/\sigma_{\rm SV} \leq 1$ form only one or two cores in a halo. In addition, HD-cooling is often enabled in models with low SV, especially in low-z, where HD-cooling is enabled in more than 50% of models. This leads to the formation of the low-mass first star. SV shapes the resulting initial mass function of the first stars and plays a critical role in setting the star-forming environment of the first galaxies., Comment: 17 pages, 13 figures, 2 tables, submitted to MNRAS

We report dispersive spin shot noise measurement of a Bose--Einstein condensate (BEC). While dispersive probing has been used for quantum spin noise measurement of thermal and cold gases for decades, confirmative measurement of spin shot noise, i.e.,\ the linear dependence of the spin variance on the number of atoms in a BEC has been lacking. Here, we demonstrate precise spin noise measurement of a BEC of rubidium atoms at the spin shot noise level by polarization rotation using a two-color probe at optimal detunings, with power balance stabilization to suppress probe-induced excess spin noise. This work opens the possibility for the unexplored study of quantum spin fluctuations in multi-component or spinor BECs and offers an approach to improve spin measurement precision, which is relevant to atomic spin-based sensors., Comment: 6 pages, 3 figures

This paper identifies the conditions and mechanisms that give rise to stochastic bubbles that are expected to collapse. To illustrate the essence of the emergence of stochastic bubbles, we first present a toy model, and then we present a full-fledged macro-finance model of intangible capital and show that stochastic stock bubbles attached to intangible capital emerge in the process of spillover of technological innovation. We show that the dynamics with stochastic bubbles, which is characterized by unbalanced growth, is a temporary deviation from a balanced growth path in which asset prices equal the fundamentals.

The observation of the kilonova AT2017gfo and investigations of its light curves and spectra confirmed that neutron star mergers are sites of r-process nucleosynthesis. However, the identification of elements responsible for the spectral features is still challenging, particularly at the near-infrared wavelengths. In this study, we systematically searched for all possible near-infrared transitions of heavy elements using experimentally calibrated energy levels. Our analysis reveals that most candidate elements with strong absorption lines are lanthanides (Z=57-71) and actinides (Z=89-103). This is due to their complex structures leading to many low-lying energy levels, which results in strong transitions in the near-infrared range. Domoto et al. (2022) have shown that La III and Ce III can explain the absorption features at $\lambda\sim$ 12,000 - 15,000 A. While our results confirm that these two elements show strong infrared features, we additionally identify Gd III as the next most promising species. Due to its unique atomic structure involving the half-filled 4f and the outer 5d orbitals, Gd III has one of the lowest-lying energy levels, between which relatively strong transitions occur. We also find absorption lines caused by Gd III in the near-infrared spectrum of a chemically peculiar star HR 465, which supports their emergence in kilonova spectra. By performing radiative transfer simulations, we confirm that Gd III lines affect the feature at $\sim$ 12,000 A previously attributed to La III. Future space-based time-series observations of kilonova spectra will allow the identification of Gd III lines., Comment: 15 pages, 9 figures, 1 table, accepted for publication in ApJ

Large models have shown unprecedented capabilities in natural language processing, image generation, and most recently, time series forecasting. This leads us to ask the question: treating market prices as a time series, can large models be used to predict the market? In this paper, we answer this by evaluating the performance of the latest time series foundation model TimesFM on price prediction. We find that due to the irregular nature of price data, directly applying TimesFM gives unsatisfactory results and propose to fine-tune TimeFM on financial data for the task of price prediction. This is done by continual pre-training of the latest time series foundation model TimesFM on price data containing 100 million time points, spanning a range of financial instruments spanning hourly and daily granularities. The fine-tuned model demonstrates higher price prediction accuracy than the baseline model. We conduct mock trading for our model in various financial markets and show that it outperforms various benchmarks in terms of returns, sharpe ratio, max drawdown and trading cost.

The initial conditions of one-dimensional expanding viscous fluids in relativistic heavy-ion collisions are scrutinized in terms of nonlinear causality of the relativistic hydrodynamic equations. Conventionally, it is believed that the matter generated in relativistic heavy-ion collisions starts to behave as a fluid all at once at some initial time. However, it is by no means trivial how soon after the first contact of two high-energy nuclei the fluid picture can be applied. It is demonstrated that one-dimensional expanding viscous fluids violate the necessary and the sufficient conditions of nonlinear causality at large departures from local equilibrium. We therefore quantify the inverse Reynolds number to justify the hydrodynamic description to be valid. The initial conditions are strictly constrained not to violate the causality conditions during the time evolution. With the help of the transverse energies per rapidity measured at RHIC and LHC, we obtain the minimum initial proper time and the maximum energy density allowed by nonlinear causality. This analysis strongly suggests that the initial stage of relativistic heavy-ion collisions needs to be described by a non-equilibrium description other than the framework of relativistic dissipative hydrodynamics., Comment: 14 pages, 9 figures; v2, updated to match the published version

The domain adaptation of language models, including large language models (LLMs), has become increasingly important as the use of such models continues to expand. This study demonstrates the effectiveness of Composition to Augment Language Models (CALM) in adapting to the financial domain. CALM is a model to extend the capabilities of existing models by introducing cross-attention between two LLMs with different functions. In our experiments, we developed a CALM to enhance the financial performance of an LLM with strong response capabilities by leveraging a financial-specialized LLM. Notably, the CALM was trained using a financial dataset different from the one used to train the financial-specialized LLM, confirming CALM's ability to adapt to various datasets. The models were evaluated through quantitative Japanese financial benchmarks and qualitative response comparisons, demonstrating that CALM enables superior responses with higher scores than the original models and baselines. Additionally, comparative experiments on connection points revealed that connecting the middle layers of the models is most effective in facilitating adaptation to the financial domain. These findings confirm that CALM is a practical approach for adapting LLMs to the financial domain.

The Atacama Large Millimeter/submillimeter Array Survey of Orion Planck Galactic Cold Clumps (ALMASOP) reveals complex nested morphological and kinematic features of molecular outflows through the CO (J = 2 - 1) and SiO (J = 5 - 4) emission. We characterize the jet and outflow kinematics of the ALMASOP sample in four representative sources (HOPS 10, 315, 358, and G203.21-11.20W2) through channel maps and position-velocity diagrams (PVDs) parallel and transverse to the outflow axes. The combined CO and SiO emission exhibits the coexistence of the conventional extremely-high-velocity (EHV) jets and shell-like low-velocity (LV) cavity walls and new features. More complex, nested bubble-like and filamentary structures in the images and channel maps, triangle-shaped regions near the base of the parallel PVDs, and regions composed of rhombus/oval shapes in the transverse PVDs, are also evident. Such features find natural explanations within the bubble structure of the unified model of jet, wind, and ambient medium. The reverse shock cavity is revealed on the PVD base regions, and other features naturally arise within the dynamic postshock region of magnetic interaction. The finer nested shells observed within the compressed wind region reveal previously unnoticed shocked emission between the jet and the conventional large cavity walls. These pseudopulse-produced filamentary features connect to the jet-like knotty blobs, creating an impression of episodicity in mass ejection. SiO emission is enhanced downstream of the reverse shock boundary, with jet-like excitation conditions. Combined, these observed features reveal the extended structures induced by the magnetic interplay between a jet-bearing magnetized wide-angle wind and its ambient magnetized surrounding medium., Comment: 27 pages, 11 figures, accepted by ApJ

This paper investigates the removal of radon from purified and ambient airs by Ag-zeolite. Ag-zeolite is known to have very high performance for airborne radon removal. The dependence of zeolite type and silver content on the performance of radon removal was evaluated. The performance of radon removal by single pass and radon emanation were also evaluated. In addition, the adsorption performance due to zeolite solidification and the change in adsorption performance due to moisture in the gas were evaluated in order to investigate properties that should be considered for future practical use. These properties will be adaptable to the development of air purification systems for the large volume ultra-low radioactivity experiments., Comment: 12 pages, 11 figures

This study aims to evaluate the sentiment of financial texts using large language models~(LLMs) and to empirically determine whether LLMs exhibit company-specific biases in sentiment analysis. Specifically, we examine the impact of general knowledge about firms on the sentiment measurement of texts by LLMs. Firstly, we compare the sentiment scores of financial texts by LLMs when the company name is explicitly included in the prompt versus when it is not. We define and quantify company-specific bias as the difference between these scores. Next, we construct an economic model to theoretically evaluate the impact of sentiment bias on investor behavior. This model helps us understand how biased LLM investments, when widespread, can distort stock prices. This implies the potential impact on stock prices if investments driven by biased LLMs become dominant in the future. Finally, we conduct an empirical analysis using Japanese financial text data to examine the relationship between firm-specific sentiment bias, corporate characteristics, and stock performance., Comment: Acceped IEEE BigData 2024 Special Sessionon Understanding New Markets by Data Science, Social Science, and Economics

In single-lined spectroscopic binaries (SB1s) where flux variations due to tidal deformation of the primary star (ellipsoidal variations, EVs) are detected, the binary mass can be determined by combining EVs with the primary's radial velocity (RV) variations from orbital motion and information about the primary's radius. This method has been used for mass estimation in close binaries including X-ray systems, but it has been pointed out that contaminating light from sources other than the primary star could introduce systematic errors in the mass and inclination estimates. Here, we focus on the apparent RV variations caused by asymmetric distortion of the absorption lines of the tidally deformed primary star (tidal RV). Because this signal contains information equivalent to that from photometric EVs, it enables mass estimation of the binary system using only the primary star's absorption lines from high-resolution spectroscopic data, providing a potentially more robust approach against contaminating light. We apply the method to the binary system V723 Monocerotis, where both photometric EV and tidal RV signals are detected, and successfully determine the component masses using only the primary star's RVs and projected rotational velocity, without relying on absolute flux measurements or on stellar evolutionary models. The masses derived from the tidal RV model show a reasonable agreement with those obtained from EVs after carefully modeling the flux contamination from the secondary. This result demonstrates that tidal RVs provide a useful alternative means for mass estimation in SB1s., Comment: 13 pages, 3 figures, accepted for publication in ApJ

Ballots are the core records of elections. Electronic records of actual ballots cast (cast vote records) are available to the public in some jurisdictions. However, they have been released in a variety of formats and have not been independently evaluated. Here we introduce a database of cast vote records from the 2020 U.S. general election. We downloaded publicly available unstandardized cast vote records, standardized them into a multi-state database, and extensively compared their totals to certified election results. Our release includes vote records for President, Governor, U.S. Senate and House, and state upper and lower chambers -- covering 42.7 million voters in 20 states who voted for more than 2,204 candidates. This database serves as a uniquely granular administrative dataset for studying voting behavior and election administration. Using this data, we show that in battleground states, 1.9 percent of solid Republicans (as defined by their congressional and state legislative voting) in our database split their ticket for Joe Biden, while 1.2 percent of solid Democrats split their ticket for Donald Trump., Comment: 26 pages and appendix

A rational bubble is a situation in which the asset price exceeds its fundamental value defined by the present value of dividends in a rational equilibrium model. We discuss the recent development of the theory of rational bubbles attached to real assets, emphasizing the following three points. (i) There exist plausible economic models in which bubbles inevitably emerge in the sense that all equilibria are bubbly. (ii) Such models are necessarily nonstationary but their long-run behavior can be analyzed using the local stable manifold theorem. (iii) Bubbles attached to real assets can naturally and necessarily arise with economic development. Finally, we present a model with stocks and land, and show that bubbles in aggregate stock and land prices necessarily emerge.

We present 850 {\mu}m thermal dust polarization observations with a resolution of 14.4"(~ 0.13 pc) towards an infrared dark cloud G16.96+0.27 using JCMT/POL-2. The average magnetic field orientation, which roughly agrees with the larger-scale magnetic field orientation traced by the Planck 353 GHz data, is approximately perpendicular to the filament structure. The estimated plane-of-sky magnetic field strength is ~ 96 {\mu}G and ~ 60 {\mu}G using two variants of the Davis-Chandrasekhar-Fermi methods. We calculate the virial and magnetic critical parameters to evaluate the relative importance of gravity, the magnetic field, and turbulence. The magnetic field and turbulence are both weaker than gravity, but magnetic fields and turbulence together are equal to gravity, suggesting that G16.96+0.27 is in a quasi-equilibrium state. The cloud-magnetic-field alignment is found to have a trend moving away from perpendicularity in the dense regions, which may serve as a tracer of potential fragmentation in such quiescent filaments., Comment: Accepted by ApJ. 13 pages, 5 figures

It has been known that stochastic gravitational wave backgrounds (SGWBs) have anisotropies generated by squeezed-type tensor non-Gaussianities originating from scalar-tensor-tensor (STT) and tensor-tensor-tensor cubic interactions. While the squeezed tensor non-Gaussianities in the standard slow-roll inflation with the Bunch-Davies vacuum state are suppressed due to the so-called consistency relation, those in extended models with the violation of the consistency relation can be enhanced. Among such extended models, we consider the inflation model with the non-Bunch-Davies state that has been known to enhance the squeezed tensor non-Gaussianities. We explicitly formulate the primordial STT bispectrum induced during inflation in the context of Horndeski theory with the non-Bunch-Davies state and show that the induced SGWB anisotropies can be enhanced. We then discuss the detectability of those anisotropies in future gravitational wave experiments., Comment: 37 pages, 4 figures

Brown dwarfs provide a unique opportunity to study atmospheres and their physical and chemical processes with high precision, especially in temperature ranges relevant to exoplanets. In this study, we performed high-resolution ($R \sim 70,000$) spectroscopy using Subaru/IRD of Gl 229 B, the first discovered T-type (T7.0p) brown dwarf, which orbits an M1V host star at a separation of 33 au. We conducted atmospheric retrieval on the reduced $H$-band spectrum using the high-resolution spectrum model compatible with automatic differentiation and GPU, ExoJAX. In contrast to previous retrieval studies on medium-resolution spectra, we obtained a C/O ratio consistent with that of the host star, aligning with the expected formation process for such a massive brown dwarf. Additionally, based on the strong constraint on temperature from the high-resolution spectrum and previously measured photometric magnitude, our analysis indicates that Gl 229 B is a binary, which was also proposed by Brandt et al. (2021). Finally, we validated current molecular line lists by leveraging the obtained high-precision, high-resolution spectrum of this warm ($\sim 900$ K) atmosphere. This study highlights the importance of observing companion brown dwarfs as benchmark objects for establishing characterization techniques for low-mass objects and enhancing our understanding of their atmospheres, given the wealth of available information and the relative ease of observation., Comment: 16 pages, 9 figures, submitted to AAS

Radon is a common background source for underground astroparticle physics experiments and its removal is essential. In this study, we fabricated several prototype silver-ion exchanged zeolites, measured their radon adsorption properties, and evaluated their applicability for radon removal in underground experiments. As a result, we succeeded in producing a prototype silver-ion exchanged zeolite that showed better radon adsorption properties than preceding studies., Comment: 14 pages, 13 figures

JASMINE is a Japanese planned space mission that aims to reveal the formation history of our Galaxy and discover habitable exoEarths. For these objectives, the JASMINE satellite performs high-precision astrometric observations of the Galactic bulge and high-precision transit monitoring of M-dwarfs in the near-infrared (1.0-1.6 microns in wavelength). For feasibility studies, we develop an image simulation software named JASMINE-imagesim, which produces realistic observation images. This software takes into account various factors such as the optical point spread function (PSF), telescope jitter caused by the satellite's attitude control error (ACE), detector flat patterns, exposure timing differences between detector pixels, and various noise factors. As an example, we report a simulation for the feasibility study of astrometric observations using JASMINE-imagesim. The simulation confirms that the required position measurement accuracy of 4 mas for a single exposure of 12.5-mag objects is achievable if the telescope pointing jitter uniformly dilutes the PSF across all stars in the field of view. On the other hand, the simulation also demonstrates that the combination of realistic pointing jitter and exposure timing differences in the detector can significantly degrade accuracy and prevent achieving the requirement. This means that certain countermeasures against this issue must be developed. This result implies that this kind of simulation is important for mission planning and advanced developments to realize more realistic simulations help us to identify critical issues and also devise effective solutions., Comment: 13 pages, 7 figures, 1 table

This paper addresses the problem of human-based driver support. Nowadays, driver support systems help users to operate safely in many driving situations. Nevertheless, these systems do not fully use the rich information that is available from sensing the human driver. In this paper, we therefore present a human-based risk model that uses driver information for improved driver support. In contrast to state of the art, our proposed risk model combines a) the current driver perception based on driver errors, such as the driver overlooking another vehicle (i.e., notice error), and b) driver personalization, such as the driver being defensive or confident. In extensive simulations of multiple interactive driving scenarios, we show that our novel human-based risk model achieves earlier warning times and reduced warning errors compared to a baseline risk model not using human driver information.

We consider the problem of human-focused driver support. State-of-the-art personalization concepts allow to estimate parameters for vehicle control systems or driver models. However, there are currently few approaches proposed that use personalized models and evaluate the effectiveness in the form of general risk warning. In this paper, we therefore propose a warning system that estimates a personalized risk factor for the given driver based on the driver's behavior. The system afterwards is able to adapt the warning signal with personalized Risk Maps. In experiments, we show examples for longitudinal following and intersection scenarios in which the novel warning system can effectively reduce false negative errors and false positive errors compared to a baseline approach which does not use personalized driver considerations. This underlines the potential of personalization for reducing warning errors in risk warning and driver support.

Expressive writing is an established approach for stress management, and recent practices include information technology. Although mobile interfaces have the potential to support daily stress management practices, interface designs for such mobile expressive writing and their effects on stress relief still lack empirical understanding. To fill the gap, we examined the interface design of mobile expressive writing by investigating the influence of input modalities and visual feedback designs on usability and perceived cathartic effects through in-the-wild studies. While our studies confirmed the stress relief effects of mobile expressive writing, our results offer important insights in interface design. We found keyboard-based text entry more user-friendly and preferred over voice messages due to its privacy friendliness and reflection process. Participants expressed different reasons for preferring different post-writing visual feedback depending on the cause and type of stress. This paper also discusses future research opportunities in interface designs for mobile expressive writing.

Inspired by the recently proposed Kolmogorov-Arnold Networks (KANs), we introduce the KAN-based Option Pricing (KANOP) model to value American-style options, building on the conventional Least Square Monte Carlo (LSMC) algorithm. KANs, which are based on Kolmogorov-Arnold representation theorem, offer a data-efficient alternative to traditional Multi-Layer Perceptrons, requiring fewer hidden layers to achieve a higher level of performance. By leveraging the flexibility of KANs, KANOP provides a learnable alternative to the conventional set of basis functions used in the LSMC model, allowing the model to adapt to the pricing task and effectively estimate the expected continuation value. Using examples of standard American and Asian-American options, we demonstrate that KANOP produces more reliable option value estimates, both for single-dimensional cases and in more complex scenarios involving multiple input variables. The delta estimated by the KANOP model is also more accurate than that obtained using conventional basis functions, which is crucial for effective option hedging. Graphical illustrations further validate KANOP's ability to accurately model the expected continuation value for American-style options.

We analyse the p--$\phi$ correlation functions in high-multiplicity proton+proton collisions at the LHC using a dynamical model, DCCI2, and discuss the effects of collision dynamics on the p--$\phi$ femtoscopic study. Collision dynamics, such as collective expansion and hadronic rescatterings, leads to the relative momentum-dependent non-Gaussian source functions. This results in deviations in the correlation functions compared to those using the Gaussian source function adopted in existing studies. Our analysis shows the importance of using the source functions that reflect more realistic collision dynamics for future precision analysis of hadron interactions via femtoscopy., Comment: 4 pages, 2 figures, proceedings of the 21st International Conference on Strangeness in Quark Matter (SQM 2024), 3-7 June 2024, Strasbourg, France

This paper proposes a novel method for constructing instruction-tuned large language models (LLMs) for finance without instruction data. Traditionally, developing such domain-specific LLMs has been resource-intensive, requiring a large dataset and significant computational power for continual pretraining and instruction tuning. Our study proposes a simpler approach that combines domain-specific continual pretraining with model merging. Given that general-purpose pretrained LLMs and their instruction-tuned LLMs are often publicly available, they can be leveraged to obtain the necessary instruction task vector. By merging this with a domain-specific pretrained vector, we can effectively create instruction-tuned LLMs for finance without additional instruction data. Our process involves two steps: first, we perform continual pretraining on financial data; second, we merge the instruction-tuned vector with the domain-specific pretrained vector. Our experiments demonstrate the successful construction of instruction-tuned LLMs for finance. One major advantage of our method is that the instruction-tuned and domain-specific pretrained vectors are nearly independent. This independence makes our approach highly effective. The Japanese financial instruction-tuned LLMs we developed in this study are available at https://huggingface.co/pfnet/nekomata-14b-pfn-qfin-inst-merge., Comment: 9 pages

We have conducted Q-band (30 GHz $-$ 50 GHz) line survey observations toward a carbon-chain emission peak in the Serpens South cluster-forming region with the extended Q-band (eQ) receiver installed on the Nobeyama 45 m radio telescope. Approximately 180 lines have been detected including tentative detection, and these lines are attributed to 52 molecules including isotopologues. It has been found that this position is rich in carbon-chain species as much as Cyanopolyyne Peak in Taurus Molecular Cloud-1 (TMC-1 CP), suggesting chemical youth. Not only carbon-chain species, but several complex organic molecules (CH$_3$OH, CH$_3$CHO, HCCCHO, CH$_3$CN, and tentatively C$_2$H$_3$CN) have also been detected, which is similar to the chemical complexity found in evolved prestellar cores. The HDCS/H$_2$CS ratio has been derived to be $11.3 \pm 0.5$ %, and this value is similar to the prestellar core L1544. The chemically young features that are similar to the less-dense starless core TMC-1 CP ($10^4$ cm$^{-3}$ $-$ $10^5$ cm$^{-3}$) and chemically evolved characters which resemble the dense prestellar core L1544 ($\sim 10^6$ cm$^{-3}$) mean that the clump including the observed position is a pre-cluster clump without any current star formation activity., Comment: Accepted for publication in Publications of the Astronomical Society of Japan (PASJ), 32 pages, 9 figures, 6 tables

HOPS 87 is a Class 0 protostellar core known to harbor an extremely young bipolar outflow and a hot corino. We report the discovery of localized, chemically rich regions near the bases of the two-lobe bipolar molecular outflow in HOPS 87 containing molecules such as H$_2$CO, $^{13}$CS, H$_2$S, OCS, and CH$_3$OH, the simplest complex organic molecule (COM). The locations and kinematics suggest that these localized features are due to jet-driven shocks rather than being part of the hot corino region encasing the protostar. The COM compositions of the molecular gas in these jet-localized regions are relatively simpler than those in the hot corino zone. We speculate that this simplicity is due to either the liberation of ice with a less complex chemical history or the effects of shock chemistry. Our study highlights the dynamic interplay between the protostellar bipolar outflow, disk, inner core environment, and the surrounding medium, contributing to our understanding of molecular complexity in solar-like young stellar objects., Comment: 16 pages, 6+2 figures, accepted by ApJ

The AI traders in financial markets have sparked significant interest in their effects on price formation mechanisms and market volatility, raising important questions for market stability and regulation. Despite this interest, a comprehensive model to quantitatively assess the specific impacts of AI traders remains undeveloped. This study aims to address this gap by modeling the influence of AI traders on market price formation and volatility within a multi-agent framework, leveraging the concept of microfoundations. Microfoundations involve understanding macroeconomic phenomena, such as market price formation, through the decision-making and interactions of individual economic agents. While widely acknowledged in macroeconomics, microfoundational approaches remain unexplored in empirical finance, particularly for models like the GARCH model, which captures key financial statistical properties such as volatility clustering and fat tails. This study proposes a multi-agent market model to derive the microfoundations of the GARCH model, incorporating three types of agents: noise traders, fundamental traders, and AI traders. By mathematically aggregating the micro-structure of these agents, we establish the microfoundations of the GARCH model. We validate this model through multi-agent simulations, confirming its ability to reproduce the stylized facts of financial markets. Finally, we analyze the impact of AI traders using parameters derived from these microfoundations, contributing to a deeper understanding of their role in market dynamics., Comment: Accepted PRIMA2024

We give explicit formulas of Whittaker functions on GL(4,R) for all irreducible generic representations. As an application, we determine test vectors which attain the associated L-factors for Bump-Friedberg integrals on GL(4,R).

We present an analytic description of the spherically symmetric gravitational collapse of radiatively cooling gas clouds, which illustrates the mechanism by which radiative cooling induces gravitational instability at a characteristic mass scale determined by the microphysics of the gas. The approach is based on developing the "one-zone" density-temperature relationship of the gas into a full dynamical model. We convert this density-temperature relationship into a barotropic equation of state, which we use to calculate the density and velocity profiles of the gas. From these quantities, we calculate the time-dependent mass accretion rate onto the center of the cloud. The approach clarifies the mechanism by which radiative cooling induces gravitational instability. In particular, we distinguish the rapid, quasi-equilibrium contraction of a cooling gas core to high central densities from the legitimate instability this contraction establishes in the envelope. We develop a refined criterion for the mass scale of this instability, based only on the chemical-thermal evolution in the core. We explicate our model in the context of a primordial mini-halo cooled by molecular hydrogen, and then provide two further examples, a delayed collapse with hydrogen deuteride cooling and the collapse of an atomic cooling halo. In all three cases, we show that our results agree well with full hydrodynamical treatments., Comment: 13+5 pages, 14+5 figures, accepted for publication in MNRAS

The transit technique has been very efficient in detecting planet candidate signals over the past decades. The so-called statistical validation approach has become a popular way of verifying a candidate's planetary nature. However, the incomplete consideration of false positive scenarios and data quality can lead to the misinterpretation of the results. In this work we revise the planetary status of K2-399\,b, a validated planet with an estimated false positive probability of 0.078% located in the middle of the so-called Neptunian desert, and hence a potential key target for atmospheric prospects. We use radial velocity data from the CARMENES, HARPS and TRES spectrographs, as well as ground-based multi-band transit photometry LCOGT MuSCAT3 and broad band photometry to test the planetary scenario. Our analysis of the available data does not support the existence of this (otherwise key) planet, and instead points to a scenario composed of an early G-dwarf orbited in a $846.62^{+0.22}_{-0.28}$~days period by a pair of eclipsing M-dwarfs (hence a hierarchical eclipsing binary) likely in the mid-type domain. We thus demote K2-399 b as a planet. We conclude that the validation process, while very useful to prioritise follow-up efforts, must always be conducted with careful attention to data quality while ensuring that all possible scenarios have been properly tested to get reliable results. We also encourage developers of validation algorithms to ensure the accuracy of a priori probabilities for different stellar scenarios that can lead to this kind of false validation. We further encourage the use of follow-up observations when possible (such as radial velocity and/or multi-band light curves) to confirm the planetary nature of detected transiting signals rather than only relying on validation tools., Comment: 14 pages, 12 figures, 5 tables, Accepted for publication in A&A Letters

Throughout history, many countries have repeatedly experienced large swings in asset prices, which are usually accompanied by large fluctuations in macroeconomic activity. One of the characteristics of the period before major economic fluctuations is the emergence of new financial products; the situation prior to the 2008 financial crisis is a prominent example of this. During that period, a variety of structured bonds, including securitized products, appeared. Because of the high returns on such financial products, many economic agents were involved in them for speculative purposes, even if they were riskier, producing macro-scale effects. With this motivation, we present a simple macroeconomic model with financial speculation. Our model illustrates two points. First, stochastic fluctuations in asset prices and macroeconomic activity are driven by the repeated appearance and disappearance of risky financial assets, rather than expansions and contractions in credit availability. Second, in an economy with sufficient borrowing and lending, the appearance of risky financial assets leads to decreased productive capital, while in an economy with severely limited borrowing and lending, it leads to increased productive capital.

We report the spectroscopic confirmation and fundamental properties of TOI-757 b, a mini-Neptune on a 17.5-day orbit transiting a bright star ($V = 9.7$ mag) discovered by the TESS mission. We acquired high-precision radial velocity measurements with the HARPS, ESPRESSO, and PFS spectrographs to confirm the planet detection and determine its mass. We also acquired space-borne transit photometry with the CHEOPS space telescope to place stronger constraints on the planet radius, supported with ground-based LCOGT photometry. WASP and KELT photometry were used to help constrain the stellar rotation period. We also determined the fundamental parameters of the host star. We find that TOI-757 b has a radius of $R_{\mathrm{p}} = 2.5 \pm 0.1 R_{\oplus}$ and a mass of $M_{\mathrm{p}} = 10.5^{+2.2}_{-2.1} M_{\oplus}$, implying a bulk density of $\rho_{\text{p}} = 3.6 \pm 0.8$ g cm$^{-3}$. Our internal composition modeling was unable to constrain the composition of TOI-757 b, highlighting the importance of atmospheric observations for the system. We also find the planet to be highly eccentric with $e$ = 0.39$^{+0.08}_{-0.07}$, making it one of the very few highly eccentric planets among precisely characterized mini-Neptunes. Based on comparisons to other similar eccentric systems, we find a likely scenario for TOI-757 b's formation to be high eccentricity migration due to a distant outer companion. We additionally propose the possibility of a more intrinsic explanation for the high eccentricity due to star-star interactions during the earlier epoch of the Galactic disk formation, given the low metallicity and older age of TOI-757., Comment: Accepted for publication in MNRAS; 26 pages, 14 figures, 6 tables

Very metal-poor stars ([Fe/H]<-2) are important laboratories for testing stellar models and reconstructing the formation history of our galaxy. Asteroseismology is a powerful tool to probe stellar interiors and measure ages, but few asteroseismic detections are known in very metal-poor stars and none have allowed detailed modeling of oscillation frequencies. We report the discovery of a low-luminosity Kepler red giant (KIC 8144907) with high S/N oscillations, [Fe/H]=-2.66+/-0.08 and [alpha/Fe]=0.38+/-0.06, making it by far the most metal-poor star to date for which detailed asteroseismic modeling is possible. By combining the oscillation spectrum from Kepler with high-resolution spectroscopy we measure an asteroseismic mass and age of 0.79+/-0.02(ran)+/-0.01(sys) Msun and 12.0+/-0.6(ran)+/-0.4(sys) Gyr, with remarkable agreement across different codes and input physics, demonstrating that stellar models and asteroseismology are reliable for very metal-poor stars when individual frequencies are used. The results also provide a direct age anchor for the early formation of the Milky Way, implying that substantial star formation did not commence until redshift z~3 (if the star formed in-situ) or that the Milky Way has undergone merger events for at least ~12 Gyr (if the star was accreted by a dwarf satellite merger such as Gaia Enceladus)., Comment: 10 pages, 4 figures, accepted for publication in ApJ

JWST has brought us new insights into Cosmic Dawn with tentative detection of the unique signatures of metal-free Population III (Pop III) stars, such as strong HeII emission, extremely blue UV spectrum, and enhanced nitrogen abundance. Self-consistent theoretical predictions of the formation rates, sites, and masses of Pop III stars are crucial for interpreting the observations, but are challenging due to complex physical processes operating over the large range of length scales involved. One solution is to combine analytical models for the small-scale star formation process with cosmological simulations that capture the large-scale physics such as structure formation, radiation backgrounds, and baryon-dark matter streaming motion that regulate the conditions of Pop III star formation. We build an analytical model to predict the final masses of Pop III stars/clusters from the properties of star-forming clouds, based on the key results of small-scale star formation simulations and stellar evolution models. Our model for the first time considers the interplay between feedback and fragmentation and covers different modes of Pop III star formation ranging from ordinary small ($\sim 10-2000\ \rm M_\odot$) clusters in molecular-cooling clouds to massive ($\gtrsim 10^{4}\ \rm M_\odot$) clusters containing supermassive ($\sim 10^{4}-3\times 10^{5}\ \rm M_\odot$) stars under violent collapse of atomic-cooling clouds. As an example, the model is applied to the Pop III star-forming clouds in the progenitors of typical haloes hosting high-$z$ luminous quasars, which shows that formation of Pop III massive clusters is common ($\sim 20-70\%$) in such biased ($\sim4\sigma$) regions, and the resulting heavy black hole seeds from supermassive stars can account for a significant fraction of observed luminous ($\gtrsim 10^{46}\ \rm erg\ s^{-1}$) quasars at $z\sim 6$., Comment: 15+8 pages, 9 + 14 figures, accepted for publication in MNRAS

"Rational bubble", as introduced by the famous paper on money by Samuelson (1958), means speculation backed by nothing. The large subsequent rational bubble literature has identified attaching bubbles to dividend-paying assets in a natural way as an important but challenging question. Miao and Wang (2018) claim to "provide a theory of rational stock price bubbles". Contrary to their claim, the present comment proves the nonexistence of rational bubbles in the model of Miao and Wang (2018). We also clarify the precise mathematical definition and the economic meaning of "rational bubble" in an accessible way to the general audience.

Magic state distillation, which is a probabilistic process used to generate magic states, plays an important role in universal fault-tolerant quantum computers. On the other hand, to solve interesting problems, we need to run complex programs on fault-tolerant quantum computers, and hence, the system needs to use hardware resources efficiently. Taking advantage of parallelism is a major optimization strategy and compilers are responsible for performing optimizations to allow parallel processing. However, the probabilistic nature of magic state distillation is not compatible with compile-time optimizations and results in an additional run-time delay. To reduce the additional run-time delay, we propose introducing a pool of magic states. We run simulations of quantum circuits to verify the magnitude of the run-time delay and the usefulness of the mitigation approach. The experimental results show that the run-time delay is amplified by parallel processing, and pooling effectively reduces the run-time delay with a small spatial cost., Comment: 13 pages, 17 figures