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High-mass binary black hole mergers from detailed binary evolution models
Authors:
Max M. Briel,
Olcay Bıyıklı,
Tassos Fragos,
Anarya Ray,
Zepei Xing,
Monica Gallegos-Garcia,
Abhishek Chattaraj,
Jeff J. Andrews,
Michael Zevin,
Vicky Kalogera,
Seth Gossage,
Philipp M. Srivastava,
Elizabeth Teng
Abstract:
Gravitational-wave observations reveal a population of binary black hole (BBH) mergers with primary masses above ${\sim}40\,\mathrm{M}_\odot$, extending into and potentially beyond the pair-instability mass gap, with a possibly flat mass-ratio and broader χ_\mathrm{eff} distribution. We investigate whether super-Eddington accretion during stable mass transfer in isolated binary evolution can produ…
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Gravitational-wave observations reveal a population of binary black hole (BBH) mergers with primary masses above ${\sim}40\,\mathrm{M}_\odot$, extending into and potentially beyond the pair-instability mass gap, with a possibly flat mass-ratio and broader χ_\mathrm{eff} distribution. We investigate whether super-Eddington accretion during stable mass transfer in isolated binary evolution can produce BBH mergers consistent with these properties across primary BH mass, mass-ratio, and χ_\mathrm{eff} distributions. Using POSYDON, we simulate BBH merger populations with primary BH masses above ${\sim}40\,\mathrm{M}_\odot$, under three BH accretion efficiencies: Eddington-limited, GRRMHD-informed, and fully conservative. We additionally vary the natal kick strength, including strong kicks at high BH masses.
We find that super-Eddington accretion does not suppress BBH mergers in the high-mass regime. Fully-conservative accretion leads to an increase of BBH mergers in POSYDON with a strong kick-independent peak at $χ_\mathrm{eff}=0.6$ and a sharp mass-ratio peak at $q\sim0.5$, whereas observations favor $χ_\mathrm{eff}=0.0$ and a flatter mass-ratio distribution. The GRRMHD-informed and Eddington-limited accretion are compatible with the observed primary BH mass and mass ratio distribution, but require natal kicks to populate negative χ_\mathrm{eff}.
A joint analysis of the primary BH mass, mass ratio, and χ_\mathrm{eff} distributions provides strong constraints on binary evolution physics, and disfavor fully-conservative BH accretion as the dominant formation mechanism for high-mass BBH mergers. The Eddington-limited and GRRMHD-informed prescriptions with modest kicks can explain part of the high-mass population, but an additional formation channel is still needed to account for the high fraction of negative χ_\mathrm{eff} systems and high secondary BH spins.
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Submitted 30 July, 2026;
originally announced July 2026.
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Stellar Population Spectra Incorporating Detailed Binary Evolution using POSYDON
Authors:
Eirini Kasdagli,
Jeff J. Andrews,
Bret Lehmer,
Rich Townsend,
Manos Zapartas,
Andreas Zezas,
Max Briel,
Tassos Fragos,
Seth Gossage,
Philipp M. Srivastava,
Elizabeth Teng
Abstract:
The accuracy of stellar population properties inferred through spectral energy distribution fitting hinges on the reliability of the underlying spectral models. Binary interactions are fundamental for massive star evolution, and ignoring their spectral contribution can lead to incorrect results. We use the POSYDON binary population synthesis code to generate spectral models of stellar populations…
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The accuracy of stellar population properties inferred through spectral energy distribution fitting hinges on the reliability of the underlying spectral models. Binary interactions are fundamental for massive star evolution, and ignoring their spectral contribution can lead to incorrect results. We use the POSYDON binary population synthesis code to generate spectral models of stellar populations that include binaries at solar metallicity. Our framework incorporates a collection of spectral libraries that is designed to address key outcomes of binary stellar evolution like Wolf-Rayet stars, stripped helium stars, and a treatment for stellar mergers. Our models confirm previous results showing that the inclusion of binary interactions has a significant effect on the UV and ionizing regime of the integrated spectrum. In particular we find that Wolf-Rayet stars and other massive stars dominate the production of ionizing radiation at earlier times, but after $\simeq$16 Myr stripped stars produced through mass transfer begin to dominate. Furthermore, we show that the production of ionizing He II photons is especially sensitive to the underlying population of stripped stars. While our results currently focus on high-mass stars ($\ge4~M_{\odot}$) at Solar metallicity, they provide the framework for binary spectral synthesis across a range of metallicities and masses and lay the foundation for calculations of the emergent emission-line spectra in the UV, optical, and IR regimes. We make the spectral models from this work publicly available for use in a format that can be integrated into fitting codes.
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Submitted 12 June, 2026; v1 submitted 11 June, 2026;
originally announced June 2026.
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Double Neutron Star Delay Times Across Cosmic Metallicities: The Role of Helium Star Progenitors
Authors:
Abhishek Chattaraj,
Jeff J. Andrews,
Max Briel,
Tassos Fragos,
Seth Gossage,
Vicky Kalogera,
Philipp M. Srivastava,
Elizabeth Teng
Abstract:
Metallicity can play a significant role in massive binary evolution through its impact on the opacity within stellar interiors and wind-driven mass loss. In this work, we investigate how the double neutron star (DNS) delay time distribution (DTD) is shaped by the metallicity-dependent evolution of the helium star$-$NS progenitor system. Drawing from insights rooted in single and binary star physic…
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Metallicity can play a significant role in massive binary evolution through its impact on the opacity within stellar interiors and wind-driven mass loss. In this work, we investigate how the double neutron star (DNS) delay time distribution (DTD) is shaped by the metallicity-dependent evolution of the helium star$-$NS progenitor system. Drawing from insights rooted in single and binary star physics, we argue that at a given metallicity, the stellar radius during the helium main-sequence sets a lower limit on the size of the DNS orbit at birth. We then perform population synthesis with the detailed binary evolution code POSYDON to illustrate the resulting DTD across a range of metallicities. Our results indicate that, independent of the common envelope efficiency and reasonable natal kicks, the majority of DNS mergers across metallicities occur typically no earlier than $\simeq 40\,\rm{Myr}$ after star formation and peaks strongly between $80-250\,\rm{Myr}$. Roughly $15\%$ of DNSs merge within 80 Myr, which may explain $r$-process enrichment in environments with brief star formation histories, while $\gtrsim 20\%$ merge on delay times $>1$Gyr, providing an explanation for short gamma-ray bursts in old, metal-poor galaxies. The shape of the DTD can be complex, with a metallicity-dependent split in the dominant formation channel imprinting a characteristic double-peaked structure. Although ideally oriented natal kicks can produce very short merging DNS, we find that the required kick magnitudes are inconsistent with observations. Our work has implications for assessing the contribution of DNS mergers to $r$-process enrichment and gamma-ray bursts/kilonovae transients across cosmic time.
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Submitted 10 June, 2026; v1 submitted 4 May, 2026;
originally announced May 2026.
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Irregularly Sampled Time Series Interpolation for Binary Evolution Simulations Using Dynamic Time Warping
Authors:
Ugur Demir,
Philipp M. Srivastava,
Aggelos Katsaggelos,
Vicky Kalogera,
Santiago L. Tapia,
Manuel Ballester,
Shamal Lalvani,
Patrick Koller,
Jeff J. Andrews,
Seth Gossage,
Max M. Briel,
Elizabeth Teng
Abstract:
Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundamental level. Producing thousands of such models requires hundreds of CPU hours, but stellar track interpolation provides one approach to significantly reduce this computational cost. Although single-star track interpolation is straightforward, stella…
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Binary stellar evolution simulations are computationally expensive. Stellar population synthesis relies on these detailed evolution models at a fundamental level. Producing thousands of such models requires hundreds of CPU hours, but stellar track interpolation provides one approach to significantly reduce this computational cost. Although single-star track interpolation is straightforward, stellar interactions in binary systems introduce significant complexity to binary evolution, making traditional single-track interpolation methods inapplicable. Binary tracks present fundamentally different challenges compared to single stars, which possess relatively straightforward evolutionary phases identifiable through distinct physical properties. Binary systems are complicated by mutual interactions that can dramatically alter evolutionary trajectories and introduce discontinuities difficult to capture through standard interpolation. In this work, we introduce a novel approach for track alignment and iterative track averaging based on Dynamic Time Warping to address misalignments between neighboring tracks. Our method computes a single shared warping path across all physical parameters simultaneously, placing them on a consistent temporal grid that preserves the causal relationships between parameters. We demonstrate that this joint-alignment strategy maintains key physical relationships such as the Stefan-Boltzmann law in the interpolated tracks. Our comprehensive evaluation across multiple binary configurations demonstrates that proper temporal alignment is crucial for track interpolation methods. The proposed method consistently outperforms existing approaches and enables the efficient generation of more accurate binary population samples for astrophysical studies.
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Submitted 15 April, 2026;
originally announced April 2026.
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A case for Case A: detailed look at binary black hole formation through stable mass transfer
Authors:
Max M. Briel,
Tassos Fragos,
Monica Gallegos-Garcia,
Anarya Ray,
Michael Zevin,
Abhishek Chattaraj,
Jeff J. Andrews,
Vicky Kalogera,
Seth Gossage,
Philipp M. Srivastava,
Elizabeth Teng
Abstract:
In isolated binary evolution, binary black hole (BBH) mergers are generally formed through stable mass transfer (SMT) or common envelope evolution. In recent years, the SMT channel has received significant attention due to detailed binary models showing increased mass transfer stability compared to previous studies. In this work, we perform a full zero-age-main-sequence to compact object merger an…
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In isolated binary evolution, binary black hole (BBH) mergers are generally formed through stable mass transfer (SMT) or common envelope evolution. In recent years, the SMT channel has received significant attention due to detailed binary models showing increased mass transfer stability compared to previous studies. In this work, we perform a full zero-age-main-sequence to compact object merger analysis using detailed binary models at eight metallicities between $10^{-4}Z_\odot$ and $2Z_\odot$ to self-consistently model the population properties of BBH mergers in the SMT channel, determined their progenitor initial conditional, and investigate the binary physics governing their formation and metallicity dependence. We use the population synthesis code POSYDON to determine the population of BBH mergers from SMT. Using its extended grids of MESA binary models, we determine the essential physics in the formation of BBH mergers. SMT produces BBH mergers predominantly from systems with $P_{ZAMS}\leq10$ days. In these systems, both the initial mass transfer between two stars and the subsequent interaction between the remaining star and the first-born BH take place while the respective donor star is on the main-sequence (Case A). We find a limited contribution from wider Case B/C systems. Without a natal kick, the SMT channel does not produce BBH mergers above $Z>0.2Z_\odot$ due to orbital widening from stellar wind mass loss. The primary BH mass distribution shows a strong dependence on metallicity, while the mass ratio prefers unity independent of metallicity due to mass ratio reversal. Additionally, the $χ_{eff}$ distributions contain peaks at $χ_{eff}=0$ and ~0.15 of which the former disappears at high metallicities. A mass-scaled natal kick leave this sub-population unchanged but introduce a low-mass, unequal mass ratio sub-population that merges due to their high eccentricity.
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Submitted 15 May, 2026; v1 submitted 3 February, 2026;
originally announced February 2026.
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A binary merger product as the direct progenitor of a Type II-P supernova
Authors:
Zexi Niu,
Ning-Chen Sun,
Emmanouil Zapartas,
Dimitris Souropanis,
Yingzhen Cui,
Justyn R. Maund,
JeffJ. Andrews,
Max M. Briel,
Morgan Fraser,
Seth Gossage,
Matthias U. Kruckow,
Camille Liotine,
Zhengwei Liu,
Philipp Podsiadlowski,
Philipp M. Srivastava,
Elizabeth Teng,
Xiaofeng Wang,
Yi Yang,
Jifeng Liu
Abstract:
Type II-P supernovae (SNe II-P) are the most common class of core-collapse SNe in the local Universe and play critical roles in many aspects of astrophysics. Since decades ago theorists have predicted that SNe II-P may originate not only from single stars but also from interacting binaries. While ~20 SNII-P progenitors have been directly detected on pre-explosion images, observational evidence sti…
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Type II-P supernovae (SNe II-P) are the most common class of core-collapse SNe in the local Universe and play critical roles in many aspects of astrophysics. Since decades ago theorists have predicted that SNe II-P may originate not only from single stars but also from interacting binaries. While ~20 SNII-P progenitors have been directly detected on pre-explosion images, observational evidence still remains scarce for this speculated binary progenitor channel. In this work, we report the discovery of a red supergiant progenitor for the Type II-P SN 2018gj. While the progenitor resembles those of other SNe II-P in terms of effective temperature and luminosity, it is located in a very old environment and SN 2018gj has an abnormally short plateau in the light curve. With state-of-the-art binary evolution simulations, we find these characteristics can only be explained if the progenitor of SN 2018gj is the merger product of a close binary system, which developed a different interior structure and evolved over a longer timescale compared with single-star evolution. This work provides the first compelling evidence for the long-sought binary progenitor channel toward SNe II-P, and our methodology serves as an innovative and pragmatic tool to motivate further investigations into this previously hidden population of SNe II-P from binaries.
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Submitted 13 January, 2026; v1 submitted 10 January, 2026;
originally announced January 2026.
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The power of binaries on stripped-envelope supernovae across metallicity: uniform progenitor parameter space and persistently low ejecta masses, but subtype diversity
Authors:
D. Souropanis,
E. Zapartas,
T. Pessi,
M. Briel,
M. Renzo,
C. P. Gutiérrez,
J. J. Andrews,
S. Gossage,
M. U. Kruckow,
C. Liotine,
P. M. Srivastava,
E. Teng
Abstract:
Stripped-envelope supernovae (SESNe) originate from massive stars that lose their envelopes through binary interactions or stellar winds. The connection between SESN subtypes and their progenitors remains poorly understood, as does the influence of initial mass, binarity, explodability, and metallicity on their evolutionary pathways, relative rates, ejecta masses, and progenitor ages. Here, we inv…
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Stripped-envelope supernovae (SESNe) originate from massive stars that lose their envelopes through binary interactions or stellar winds. The connection between SESN subtypes and their progenitors remains poorly understood, as does the influence of initial mass, binarity, explodability, and metallicity on their evolutionary pathways, relative rates, ejecta masses, and progenitor ages. Here, we investigate these properties across a wide metallicity range (0.01-2 $Z_{\odot}$) using POSYDON, a state-of-the-art population synthesis code that incorporates detailed single- and binary-star model grids. We find that the common-envelope channel contributes less than 6% of SESNe, since unstable mass transfer is found less frequent than previously thought and rarely leads to CE survival when envelope binding energies are computed from detailed stellar models. The secondary channel accounts for less than 11%, while the vast majority of SESNe originate from primary stars in binaries undergoing stable mass-transfer episodes. These interactions maintain a largely metallicity-independent SESN parameter space, making the overall SESN rate almost insensitive to metallicity. In contrast, subtype fractions exhibit strong metallicity dependence, though their exact values remain affected by classification thresholds. The age distributions and therefore the progenitor masses of different SESN types also vary significantly with metallicity, revealing metallicity-dependent trends that can be tested observationally. Predicted SESN ejecta masses remain nearly constant across metallicity, in contrast to single-star models, and fall within observed ranges. Future transient surveys, combined with statistical environmental studies that constrain metallicity dependence, will provide decisive tests of these predictions and of the dominant role of binary interactions in shaping SESNe.
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Submitted 28 August, 2025;
originally announced August 2025.
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HST Deep Upper Limits Rule Out a Surviving Massive Binary Companion to the Type Ic Supernova 2012fh
Authors:
Benjamin F. Williams,
Emmanouil Zapartas,
Ori D. Fox,
K. Azalee Bostroem,
Jianing Su,
Brad Koplitz,
Schuyler D. Van Dyk,
Maria R. Drout,
Dimitris Souropanis,
Dan Milisavljevic,
Stuart D. Ryder,
Selma E. de Mink,
Nathan Smith,
Andrew Dolphin,
Alexei V. Filippenko,
Jeff J. Andrews,
Max M. Briel,
Seth Gossage,
Matthias U. Kruckow,
Camille Liotine,
Philipp M. Srivastava,
Elizabeth Teng
Abstract:
Current explanations of the mass-loss mechanism for stripped-envelope supernovae remain divided between single and binary progenitor systems. Here we obtain deep ultraviolet (UV) imaging with the Hubble Space Telescope (HST) of the Type Ic SN 2012fh to search for the presence of a surviving companion star to the progenitor. We synthesize these observations with archival HST imaging, ground-based s…
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Current explanations of the mass-loss mechanism for stripped-envelope supernovae remain divided between single and binary progenitor systems. Here we obtain deep ultraviolet (UV) imaging with the Hubble Space Telescope (HST) of the Type Ic SN 2012fh to search for the presence of a surviving companion star to the progenitor. We synthesize these observations with archival HST imaging, ground-based spectroscopy, and previous analyses from the literature to provide three independent constraints on the progenitor system. We fit the color-magnitude diagram of the surrounding population to constrain the most likely age of the system to be $<20$ Myr. Analysis of spectra of SN 2012fh provide an estimate of the He core mass of the progenitor star, $>5.6$ M$_{\odot}$. We analyze deep HST images at the precise location after the SN faded to constrain the luminosity of any remaining main-sequence binary companion to be $\log(L/L_{\odot}) \lesssim 3.35$. Combining observational constraints with current binary population synthesis models excludes the presence of a faint stellar companion to SN 2012fh at the $\lesssim10\%$ level. The progenitor was therefore either effectively isolated at the time of explosion or orbited by a black-hole companion. The latter scenario dominates if we only consider models that produce successful supernovae.
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Submitted 19 September, 2025; v1 submitted 28 August, 2025;
originally announced August 2025.
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The Demographics of Binary Companions to Stripped-Envelope Supernovae: Confronting Observations with Population Synthesis
Authors:
E. Zapartas,
O. D. Fox,
J. Su,
D. Souropanis,
M. R. Drout,
K. A. Rocha,
S. D. van Dyk,
B. F. Williams,
M. Briel,
M. Renzo,
J. J. Andrews,
T. Fragos,
S. Gossage,
M. U. Kruckow,
C. Liotine,
S. D. Ryder,
P. M. Srivastava,
E. Teng
Abstract:
Stripped-envelope supernovae (SESNe) mark the deaths of massive stars without hydrogen-rich envelopes. Most SESNe likely originate from binary systems where a companion stripped the progenitor of its envelope. Years of HST imaging of nearby SESNe sites have produced a statistically meaningful sample of constraints on surviving binary companions. We assemble the current sample of six companion dete…
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Stripped-envelope supernovae (SESNe) mark the deaths of massive stars without hydrogen-rich envelopes. Most SESNe likely originate from binary systems where a companion stripped the progenitor of its envelope. Years of HST imaging of nearby SESNe sites have produced a statistically meaningful sample of constraints on surviving binary companions. We assemble the current sample of six companion detections and six non-detections from the literature, re-analyzing whenever needed. We then conduct the first statistical comparison with binary population-synthesis predictions, primarily based on new calculations performed with the POSYDON framework. Across a metallicity range, our models predict that 80-90% of Type Ib/c and 60-85% of IIb SNe explode with a rapidly rotating, main-sequence companion. The observed luminosity distribution favors fairly inefficient mass accretion and failed explosions of the most massive stripped stars. The companion detection fraction broadly matches predictions, given the imaging depth, but appears elevated for Type IIb SNe. In all but one non-detection, a faint, undetected companion is the most likely scenario. The red, apparently evolved companions in a few Type Ib/c SNe may result from strong interaction with the ejecta, expected in $\sim$12% of them. Companion demographics offer a powerful, independent probe of SESN progenitor systems, with the current sample disfavoring efficient accretion and supporting Wolf-Rayet non-explodability. Larger companion samples and follow-up studies will further clarify binary pathways to SESNe, serving as benchmarks for transient surveys.
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Submitted 18 August, 2025;
originally announced August 2025.
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Forming Double Neutron Stars using Detailed Binary Evolution Models with POSYDON: Comparison to the Galactic Systems
Authors:
Abhishek Chattaraj,
Jeff J. Andrews,
Simone S. Bavera,
Max Briel,
Debatri Chattopadhyay,
Tassos Fragos,
Seth Gossage,
Vicky Kalogera,
Konstantinos Kovlakas,
Matthias U. Kruckow,
Camille Liotine,
Kyle A. Rocha,
Philipp M. Srivastava,
Meng Sun,
Elizabeth Teng,
Zepei Xing,
Emmanouil Zapartas
Abstract:
With over two dozen detections in the Milky Way, double neutron stars (DNSs) provide a unique window into massive binary evolution. We use the POSYDON binary population synthesis code to model DNS populations and compare them to the observed Galactic sample. By tracing their origins to underlying single and binary star physics, we place constraints on the detailed evolutionary stages leading to DN…
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With over two dozen detections in the Milky Way, double neutron stars (DNSs) provide a unique window into massive binary evolution. We use the POSYDON binary population synthesis code to model DNS populations and compare them to the observed Galactic sample. By tracing their origins to underlying single and binary star physics, we place constraints on the detailed evolutionary stages leading to DNS formation. Our study reveals a bifurcation within the well-known common envelope (CE) formation channel for DNSs, which naturally explains an observed split in the orbital periods of the Galactic systems. The two subchannels are defined by whether the donor star has a helium core (Case B mass transfer) or a carbon-oxygen core (Case C) at the onset of the CE, with only the helium core systems eventually merging due to gravitational wave-modulated orbital decay. We find that across different treatments of the CE phase, the formation of DNSs through both subchannels requires either a generous core definition of $\simeq$ 30% H-fraction or a high CE ejection efficiency of $α_{\rm CE}\gtrsim1.2$. By testing different supernova kick velocity models, we find that galactic DNSs are best reproduced using a prescription that favors low velocity kicks ($\lesssim 50 \, \rm km/s$), in agreement with previous studies. Furthermore, our models indicate that merging DNSs are born from a stripped progenitor with a median pre-supernova envelope mass $\sim$ 0.2$M_{\odot}$. Our results highlight the value of detailed evolutionary models for improving our understanding of exotic binary star formation.
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Submitted 10 June, 2026; v1 submitted 31 July, 2025;
originally announced August 2025.
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Giant Outer Transiting Exoplanet Mass (GOT 'EM) Survey. VI: Confirmation of a Long-Period Giant Planet Discovered with a Single TESS Transit
Authors:
Zahra Essack,
Diana Dragomir,
Paul A. Dalba,
Matthew P. Battley,
David R. Ciardi,
Karen A. Collins,
Steve B. Howell,
Matias I. Jones,
Stephen R. Kane,
Eric E. Mamajek,
Christopher R. Mann,
Ismael Mireles,
Dominic Oddo,
Lauren A. Sgro,
Keivan G. Stassun,
Solene Ulmer-Moll,
Cristilyn N. Watkins,
Samuel W. Yee,
Carl Ziegler,
Allyson Bieryla,
Ioannis Apergis,
Khalid Barkaoui,
Rafael Brahm,
Edward M. Bryant,
Thomas M. Esposito
, et al. (59 additional authors not shown)
Abstract:
We report the discovery and confirmation of TOI-4465 b, a $1.25^{+0.08}_{-0.07}~R_{J}$, $5.89\pm0.26~M_{J}$ giant planet orbiting a G dwarf star at $d\simeq$ 122 pc. The planet was detected as a single-transit event in data from Sector 40 of the Transiting Exoplanet Survey Satellite (TESS) mission. Radial velocity (RV) observations of TOI-4465 showed a planetary signal with an orbital period of…
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We report the discovery and confirmation of TOI-4465 b, a $1.25^{+0.08}_{-0.07}~R_{J}$, $5.89\pm0.26~M_{J}$ giant planet orbiting a G dwarf star at $d\simeq$ 122 pc. The planet was detected as a single-transit event in data from Sector 40 of the Transiting Exoplanet Survey Satellite (TESS) mission. Radial velocity (RV) observations of TOI-4465 showed a planetary signal with an orbital period of $\sim$102 days, and an orbital eccentricity of $e=0.24\pm0.01$. TESS re-observed TOI-4465 in Sector 53 and Sector 80, but did not detect another transit of TOI-4465 b, as the planet was not expected to transit during these observations based on the RV period. A global ground-based photometry campaign was initiated to observe another transit of TOI-4465 b after the RV period determination. The $\sim$12 hour-long transit event was captured from multiple sites around the world, and included observations from 24 citizen scientists, confirming the orbital period as $\sim$102 days. TOI-4465 b is a relatively dense ($3.73\pm0.53~\rm{g/cm^3}$), temperate (375-478 K) giant planet. Based on giant planet structure models, TOI-4465 b appears to be enriched in heavy elements at a level consistent with late-stage accretion of icy planetesimals. Additionally, we explore TOI-4465 b's potential for atmospheric characterization, and obliquity measurement. Increasing the number of long-period planets by confirming single-transit events is crucial for understanding the frequency and demographics of planet populations in the outer regions of planetary systems.
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Submitted 24 June, 2025;
originally announced June 2025.
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Challenges in Forming Millisecond Pulsar-Black Holes from Isolated Binaries
Authors:
Camille Liotine,
Vicky Kalogera,
Jeff J. Andrews,
Simone S. Bavera,
Max Briel,
Tassos Fragos,
Seth Gossage,
Konstantinos Kovlakas,
Matthias U. Kruckow,
Kyle A. Rocha,
Philipp M. Srivastava,
Meng Sun,
Elizabeth Teng,
Zepei Xing,
Emmanouil Zapartas
Abstract:
Binaries harboring a millisecond pulsar (MSP) and a black hole (BH) are a key observing target for current and upcoming pulsar surveys. We model the formation and evolution of such binaries in isolation at solar metallicity using the next-generation binary population synthesis code POSYDON. We examine neutron star (NS)-BH binaries where the NS forms first (labeled NSBH), as the NS must be able to…
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Binaries harboring a millisecond pulsar (MSP) and a black hole (BH) are a key observing target for current and upcoming pulsar surveys. We model the formation and evolution of such binaries in isolation at solar metallicity using the next-generation binary population synthesis code POSYDON. We examine neutron star (NS)-BH binaries where the NS forms first (labeled NSBH), as the NS must be able to spin-up to MSP rotation periods before the BH forms in these systems. We find that NSBHs are very rare and have a birth rate < 1 Myr$^{-1}$ for a Milky Way-like galaxy in our typical models. The NSBH birth rate is 2-3 orders of magnitude smaller than that for NS-BHs where the BH forms first (labeled BHNS). These rates are also sensitive to model assumptions about the supernova (SN) remnant masses, natal kicks, and common-envelope efficiency. We find that 100% of NSBHs undergo a mass ratio reversal before the first SN and up to 64% of NSBHs undergo a double common envelope phase after the mass ratio reversal occurs. Most importantly, no NSBH binaries in our populations undergo a mass transfer phase, either stable or unstable, after the first SN. This implies that there is no possibility of pulsar spin-up via accretion, and thus MSP-BH binaries cannot form. Thus, dynamical environments and processes may provide the only formation channels for such MSP-BH binaries.
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Submitted 19 December, 2024;
originally announced December 2024.
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Irregularly Sampled Time Series Interpolation for Detailed Binary Evolution Simulations
Authors:
Philipp M. Srivastava,
Ugur Demir,
Aggelos Katsaggelos,
Vicky Kalogera,
Elizabeth Teng,
Tassos Fragos,
Jeff J. Andrews,
Simone S. Bavera,
Max Briel,
Seth Gossage,
Konstantinos Kovlakas,
Matthias U. Kruckow,
Camille Liotine,
Kyle A. Rocha,
Meng Sun,
Zepei Xing,
Emmanouil Zapartas
Abstract:
Modeling of large populations of binary stellar systems is an intergral part of a many areas of astrophysics, from radio pulsars and supernovae to X-ray binaries, gamma-ray bursts, and gravitational-wave mergers. Binary population synthesis codes that employ self-consistently the most advanced physics treatment available for stellar interiors and their evolution and are at the same time computatio…
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Modeling of large populations of binary stellar systems is an intergral part of a many areas of astrophysics, from radio pulsars and supernovae to X-ray binaries, gamma-ray bursts, and gravitational-wave mergers. Binary population synthesis codes that employ self-consistently the most advanced physics treatment available for stellar interiors and their evolution and are at the same time computationally tractable have started to emerge only recently. One element that is still missing from these codes is the ability to generate the complete time evolution of binaries with arbitrary initial conditions using pre-computed three-dimensional grids of binary sequences. Here we present a highly interpretable method, from binary evolution track interpolation. Our method implements simulation generation from irregularly sampled time series. Our results indicate that this method is appropriate for applications within binary population synthesis and computational astrophysics with time-dependent simulations in general. Furthermore we point out and offer solutions to the difficulty surrounding evaluating performance of signals exhibiting extreme morphologies akin to discontinuities.
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Submitted 4 November, 2024;
originally announced November 2024.
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POSYDON Version 2: Population Synthesis with Detailed Binary-Evolution Simulations across a Cosmological Range of Metallicities
Authors:
Jeff J. Andrews,
Simone S. Bavera,
Max Briel,
Abhishek Chattaraj,
Aaron Dotter,
Tassos Fragos,
Monica Gallegos-Garcia,
Seth Gossage,
Vicky Kalogera,
Eirini Kasdagli,
Aggelos Katsaggelos,
Chase Kimball,
Konstantinos Kovlakas,
Matthias U. Kruckow,
Camille Liotine,
Devina Misra,
Kyle A. Rocha,
Dimitris Souropanis,
Philipp M. Srivastava,
Meng Sun,
Elizabeth Teng,
Zepei Xing,
Emmanouil Zapartas,
Michael Zevin
Abstract:
Whether considering rare astrophysical events on cosmological scales or unresolved stellar populations, accurate models must account for the integrated contribution from the entire history of star formation upon which that population is built. Here, we describe the second version of POSYDON, an open-source binary population synthesis code based on extensive grids of detailed binary evolution model…
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Whether considering rare astrophysical events on cosmological scales or unresolved stellar populations, accurate models must account for the integrated contribution from the entire history of star formation upon which that population is built. Here, we describe the second version of POSYDON, an open-source binary population synthesis code based on extensive grids of detailed binary evolution models computed using the MESA code, which follows both stars' structures as a binary system evolves through its complete evolution from the zero-age main sequence, through multiple phases of mass transfer and supernovae, to their death as compact objects. To generate synthetic binary populations, POSYDON uses advanced methods to interpolate between our large, densely spaced grids of simulated binaries. In our updated version of POSYDON, we account for the evolution of stellar binaries across a cosmological range of metallicities, extending from $10^{-4}$ $Z_{\odot}$ to 2 $Z_{\odot}$, including grids specifically focused on the Small and Large Magellanic Clouds (0.2 $Z_{\odot}$ and 0.45 $Z_{\odot}$). In addition to describing our model grids and detailing our methodology, we outline several improvements to POSYDON. These include the incorporation of single stars in stellar populations, a treatment for stellar mergers, and a careful modeling of "reverse-mass transferring" binaries in which a once-accreting star later becomes a donor star. Our simulations are focused on binaries with at least one high-mass component, such as those that host neutron stars and black holes, and we provide post-processing methods to account for the cosmological evolution of metallicity and star formation as well as rate calculations for transient events.
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Submitted 11 August, 2025; v1 submitted 4 November, 2024;
originally announced November 2024.
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Emulators for stellar profiles in binary population modeling
Authors:
Elizabeth Teng,
Ugur Demir,
Zoheyr Doctor,
Philipp M. Srivastava,
Shamal Lalvani,
Vicky Kalogera,
Aggelos Katsaggelos,
Jeff J. Andrews,
Simone S. Bavera,
Max M. Briel,
Seth Gossage,
Konstantinos Kovlakas,
Matthias U. Kruckow,
Kyle Akira Rocha,
Meng Sun,
Zepei Xing,
Emmanouil Zapartas
Abstract:
Knowledge about the internal physical structure of stars is crucial to understanding their evolution. The novel binary population synthesis code POSYDON includes a module for interpolating the stellar and binary properties of any system at the end of binary MESA evolution based on a pre-computed set of models. In this work, we present a new emulation method for predicting stellar profiles, i.e., t…
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Knowledge about the internal physical structure of stars is crucial to understanding their evolution. The novel binary population synthesis code POSYDON includes a module for interpolating the stellar and binary properties of any system at the end of binary MESA evolution based on a pre-computed set of models. In this work, we present a new emulation method for predicting stellar profiles, i.e., the internal stellar structure along the radial axis, using machine learning techniques. We use principal component analysis for dimensionality reduction and fully-connected feed-forward neural networks for making predictions. We find accuracy to be comparable to that of nearest neighbor approximation, with a strong advantage in terms of memory and storage efficiency. By providing a versatile framework for modeling stellar internal structure, the emulation method presented here will enable faster simulations of higher physical fidelity, offering a foundation for a wide range of large-scale population studies of stellar and binary evolution.
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Submitted 11 February, 2025; v1 submitted 14 October, 2024;
originally announced October 2024.
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Single-shot readout of the nuclear spin of an on-surface atom
Authors:
Evert W. Stolte,
Jinwon Lee,
Hester G. Vennema,
Rik Broekhoven,
Esther Teng,
Allard J. Katan,
Lukas M. Veldman,
Philip Willke,
Sander Otte
Abstract:
Nuclear spins owe their long-lived magnetic states to their excellent isolation from the environment. At the same time, a finite degree of interaction with their surroundings is necessary for reading and writing the spin state. Therefore, detailed knowledge of and control over the atomic environment of a nuclear spin is key to optimizing conditions for quantum information applications. While vario…
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Nuclear spins owe their long-lived magnetic states to their excellent isolation from the environment. At the same time, a finite degree of interaction with their surroundings is necessary for reading and writing the spin state. Therefore, detailed knowledge of and control over the atomic environment of a nuclear spin is key to optimizing conditions for quantum information applications. While various platforms enabled single-shot readout of nuclear spins, their direct environments were either unknown or impossible to controllably modify on the atomic scale. Scanning tunnelling microscopy (STM), combined with electron spin resonance (ESR), provides atomic-scale information of individual nuclear spins via the hyperfine interaction. Here, we demonstrate single-shot readout of an individual $^{\text{49}}$Ti nuclear spin with an STM. Employing a pulsed measurement scheme, we find its lifetime to be in the order of seconds. Furthermore, we shed light on the pumping and relaxation mechanisms of the nuclear spin by investigating its response to both ESR driving and tunnelling current, which is supported by model calculations. These findings give an atomic-scale insight into the nature of nuclear spin relaxation and are relevant for the development of atomically assembled qubit platforms.
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Submitted 21 August, 2025; v1 submitted 11 October, 2024;
originally announced October 2024.
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A Detection of Red Noise in PSR J1824$-$2452A and Projections for PSR B1937+21 using NICER X-ray Timing Data
Authors:
Jeffrey S. Hazboun,
Jack Crump,
Andrea N. Lommen,
Sergio Montano,
Samantha J. H. Berry,
Jesse Zeldes,
Elizabeth Teng,
Paul S. Ray,
Matthew Kerr,
Zaven Arzoumanian,
Slavko Bogdanov,
Julia Deneva,
Natalia Lewandowska,
Craig B. Markwardt,
Scott Ransom,
Teruaki Enoto,
Kent S. Wood,
Keith C. Gendreau,
David A. Howe,
Aditya Parthasarathy
Abstract:
We have used X-ray data from the Neutron Star Interior Composition Explorer (NICER) to search for long time-scale, correlated variations ("red noise") in the pulse times of arrival from the millisecond pulsars PSR J1824$-$2452A and PSR B1937+21. These data more closely track intrinsic noise because X-rays are unaffected by the radio-frequency dependent propagation effects of the interstellar mediu…
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We have used X-ray data from the Neutron Star Interior Composition Explorer (NICER) to search for long time-scale, correlated variations ("red noise") in the pulse times of arrival from the millisecond pulsars PSR J1824$-$2452A and PSR B1937+21. These data more closely track intrinsic noise because X-rays are unaffected by the radio-frequency dependent propagation effects of the interstellar medium. Our Bayesian search methodology yields strong evidence (natural log Bayes factor of $9.634 \pm 0.016$) for red noise in PSR J1824$-$2452A, but is inconclusive for PSR B1937+21. In the interest of future X-ray missions, we devise and implement a method to simulate longer and higher precision X-ray datasets to determine the timing baseline necessary to detect red noise. We find that the red noise in PSR B1937+21 can be reliably detected in a 5-year mission with a time-of-arrival (TOA) error of 2 microseconds and an observing cadence of 20 observations per month compared to the 5 microsecond TOA error and 11 observations per month that NICER currently achieves in PSR B1937+21. We investigate detecting red noise in PSR B1937+21 with other combinations of observing cadences and TOA errors. We also find that an injected stochastic gravitational wave background (GWB) with an amplitude of $A_{\rm GWB}=2\times10^{-15}$ and spectral index of $γ_{\rm GWB}=13/3$ can be detected in a pulsar with similar TOA precision to PSR B1937+21, but with no additional red noise, in a 10-year mission that observes the pulsar 15 times per month and has an average TOA error of 1 microsecond.
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Submitted 3 December, 2021;
originally announced December 2021.
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On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning
Authors:
Andrew Cohen,
Ervin Teng,
Vincent-Pierre Berges,
Ruo-Ping Dong,
Hunter Henry,
Marwan Mattar,
Alexander Zook,
Sujoy Ganguly
Abstract:
The creation and destruction of agents in cooperative multi-agent reinforcement learning (MARL) is a critically under-explored area of research. Current MARL algorithms often assume that the number of agents within a group remains fixed throughout an experiment. However, in many practical problems, an agent may terminate before their teammates. This early termination issue presents a challenge: th…
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The creation and destruction of agents in cooperative multi-agent reinforcement learning (MARL) is a critically under-explored area of research. Current MARL algorithms often assume that the number of agents within a group remains fixed throughout an experiment. However, in many practical problems, an agent may terminate before their teammates. This early termination issue presents a challenge: the terminated agent must learn from the group's success or failure which occurs beyond its own existence. We refer to propagating value from rewards earned by remaining teammates to terminated agents as the Posthumous Credit Assignment problem. Current MARL methods handle this problem by placing these agents in an absorbing state until the entire group of agents reaches a termination condition. Although absorbing states enable existing algorithms and APIs to handle terminated agents without modification, practical training efficiency and resource use problems exist.
In this work, we first demonstrate that sample complexity increases with the quantity of absorbing states in a toy supervised learning task for a fully connected network, while attention is more robust to variable size input. Then, we present a novel architecture for an existing state-of-the-art MARL algorithm which uses attention instead of a fully connected layer with absorbing states. Finally, we demonstrate that this novel architecture significantly outperforms the standard architecture on tasks in which agents are created or destroyed within episodes as well as standard multi-agent coordination tasks.
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Submitted 6 June, 2022; v1 submitted 10 November, 2021;
originally announced November 2021.
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Autonomous Curiosity for Real-Time Training Onboard Robotic Agents
Authors:
Ervin Teng,
Bob Iannucci
Abstract:
Learning requires both study and curiosity. A good learner is not only good at extracting information from the data given to it, but also skilled at finding the right new information to learn from. This is especially true when a human operator is required to provide the ground truth - such a source should only be queried sparingly. In this work, we address the problem of curiosity as it relates to…
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Learning requires both study and curiosity. A good learner is not only good at extracting information from the data given to it, but also skilled at finding the right new information to learn from. This is especially true when a human operator is required to provide the ground truth - such a source should only be queried sparingly. In this work, we address the problem of curiosity as it relates to online, real-time, human-in-the-loop training of an object detection algorithm onboard a robotic platform, one where motion produces new views of the subject. We propose a deep reinforcement learning approach that decides when to ask the human user for ground truth, and when to move. Through a series of experiments, we demonstrate that our agent learns a movement and request policy that is at least 3x more effective at using human user interactions to train an object detector than untrained approaches, and is generalizable to a variety of subjects and environments.
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Submitted 29 August, 2021;
originally announced September 2021.
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Learning to Learn in Simulation
Authors:
Ervin Teng,
Bob Iannucci
Abstract:
Deep learning often requires the manual collection and annotation of a training set. On robotic platforms, can we partially automate this task by training the robot to be curious, i.e., to seek out beneficial training information in the environment? In this work, we address the problem of curiosity as it relates to online, real-time, human-in-the-loop training of an object detection algorithm onbo…
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Deep learning often requires the manual collection and annotation of a training set. On robotic platforms, can we partially automate this task by training the robot to be curious, i.e., to seek out beneficial training information in the environment? In this work, we address the problem of curiosity as it relates to online, real-time, human-in-the-loop training of an object detection algorithm onboard a drone, where motion is constrained to two dimensions. We use a 3D simulation environment and deep reinforcement learning to train a curiosity agent to, in turn, train the object detection model. This agent could have one of two conflicting objectives: train as quickly as possible, or train with minimal human input. We outline a reward function that allows the curiosity agent to learn either of these objectives, while taking into account some of the physical characteristics of the drone platform on which it is meant to run. In addition, We show that we can weigh the importance of achieving these objectives by adjusting a parameter in the reward function.
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Submitted 5 February, 2019;
originally announced February 2019.
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Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning
Authors:
Arthur Juliani,
Ahmed Khalifa,
Vincent-Pierre Berges,
Jonathan Harper,
Ervin Teng,
Hunter Henry,
Adam Crespi,
Julian Togelius,
Danny Lange
Abstract:
The rapid pace of recent research in AI has been driven in part by the presence of fast and challenging simulation environments. These environments often take the form of games; with tasks ranging from simple board games, to competitive video games. We propose a new benchmark - Obstacle Tower: a high fidelity, 3D, 3rd person, procedurally generated environment. An agent playing Obstacle Tower must…
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The rapid pace of recent research in AI has been driven in part by the presence of fast and challenging simulation environments. These environments often take the form of games; with tasks ranging from simple board games, to competitive video games. We propose a new benchmark - Obstacle Tower: a high fidelity, 3D, 3rd person, procedurally generated environment. An agent playing Obstacle Tower must learn to solve both low-level control and high-level planning problems in tandem while learning from pixels and a sparse reward signal. Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment. In this paper we outline the environment and provide a set of baseline results produced by current state-of-the-art Deep RL methods as well as human players. These algorithms fail to produce agents capable of performing near human level.
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Submitted 1 July, 2019; v1 submitted 4 February, 2019;
originally announced February 2019.
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Unity: A General Platform for Intelligent Agents
Authors:
Arthur Juliani,
Vincent-Pierre Berges,
Ervin Teng,
Andrew Cohen,
Jonathan Harper,
Chris Elion,
Chris Goy,
Yuan Gao,
Hunter Henry,
Marwan Mattar,
Danny Lange
Abstract:
Recent advances in artificial intelligence have been driven by the presence of increasingly realistic and complex simulated environments. However, many of the existing environments provide either unrealistic visuals, inaccurate physics, low task complexity, restricted agent perspective, or a limited capacity for interaction among artificial agents. Furthermore, many platforms lack the ability to f…
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Recent advances in artificial intelligence have been driven by the presence of increasingly realistic and complex simulated environments. However, many of the existing environments provide either unrealistic visuals, inaccurate physics, low task complexity, restricted agent perspective, or a limited capacity for interaction among artificial agents. Furthermore, many platforms lack the ability to flexibly configure the simulation, making the simulated environment a black-box from the perspective of the learning system. In this work, we propose a novel taxonomy of existing simulation platforms and discuss the highest level class of general platforms which enable the development of learning environments that are rich in visual, physical, task, and social complexity. We argue that modern game engines are uniquely suited to act as general platforms and as a case study examine the Unity engine and open source Unity ML-Agents Toolkit. We then survey the research enabled by Unity and the Unity ML-Agents Toolkit, discussing the kinds of research a flexible, interactive and easily configurable general platform can facilitate.
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Submitted 6 May, 2020; v1 submitted 7 September, 2018;
originally announced September 2018.
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ClickBAIT-v2: Training an Object Detector in Real-Time
Authors:
Ervin Teng,
Rui Huang,
Bob Iannucci
Abstract:
Modern deep convolutional neural networks (CNNs) for image classification and object detection are often trained offline on large static datasets. Some applications, however, will require training in real-time on live video streams with a human-in-the-loop. We refer to this class of problem as time-ordered online training (ToOT). These problems will require a consideration of not only the quantity…
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Modern deep convolutional neural networks (CNNs) for image classification and object detection are often trained offline on large static datasets. Some applications, however, will require training in real-time on live video streams with a human-in-the-loop. We refer to this class of problem as time-ordered online training (ToOT). These problems will require a consideration of not only the quantity of incoming training data, but the human effort required to annotate and use it. We demonstrate and evaluate a system tailored to training an object detector on a live video stream with minimal input from a human operator. We show that we can obtain bounding box annotation from weakly-supervised single-point clicks through interactive segmentation. Furthermore, by exploiting the time-ordered nature of the video stream through object tracking, we can increase the average training benefit of human interactions by 3-4 times.
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Submitted 27 March, 2018;
originally announced March 2018.
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ClickBAIT: Click-based Accelerated Incremental Training of Convolutional Neural Networks
Authors:
Ervin Teng,
João Diogo Falcão,
Bob Iannucci
Abstract:
Today's general-purpose deep convolutional neural networks (CNN) for image classification and object detection are trained offline on large static datasets. Some applications, however, will require training in real-time on live video streams with a human-in-the-loop. We refer to this class of problem as Time-ordered Online Training (ToOT) - these problems will require a consideration of not only t…
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Today's general-purpose deep convolutional neural networks (CNN) for image classification and object detection are trained offline on large static datasets. Some applications, however, will require training in real-time on live video streams with a human-in-the-loop. We refer to this class of problem as Time-ordered Online Training (ToOT) - these problems will require a consideration of not only the quantity of incoming training data, but the human effort required to tag and use it. In this paper, we define training benefit as a metric to measure the effectiveness of a sequence in using each user interaction. We demonstrate and evaluate a system tailored to performing ToOT in the field, capable of training an image classifier on a live video stream through minimal input from a human operator. We show that by exploiting the time-ordered nature of the video stream through optical flow-based object tracking, we can increase the effectiveness of human actions by about 8 times.
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Submitted 14 September, 2017;
originally announced September 2017.