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Analytical methods defining location of reference horizons in earth horizon radiance profile
X-Band Scanning ARM Cloud Radar (XSACR) Hemispherical Sky RHI Scans (6 horizon-to-horizon scans at 30-degree azimuth intervals) Corrected
Feasibility design of instrument system to collect data of horizon radiance profile in carbon dioxide absorption band
Earth infrared horizon definition for space guidance, navigation, control, and pointing systems - feasibility study
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A major limitation on the use of infrared horizon sensors for attitude determination is the variability of the height of the infrared Earth horizon. This variation includes a climatological component and a stochastic component of approximately equal importance. The climatological component shows regular variation with season and latitude. Models based on historical measurements have been used to compensate for these systematic changes. The stochastic component is analogous to tropospheric weather. It can cause extreme, localized changes that for a period of days, overwhelm the climatological variation. An algorithm has been developed to compensate partially for the climatological variation of horizon height and at least to mitigate the stochastic variation. This method uses attitude and horizon sensor data from spacecraft to update a horizon height history as a function of latitude. For spacecraft that depend on horizon sensors for their attitudes (such as the Total Ozone Mapping Spectrometer-Earth Probe-TOMS-EP) a batch least squares attitude determination system is used. It is assumed that minimizing the average sensor residual throughout a full orbit of data results in attitudes that are nearly independent of local horizon height variations. The method depends on the additional assumption that the mean horizon height over all latitudes is approximately independent of season. Using these assumptions, the method yields the latitude dependent portion of local horizon height variations. This paper describes the algorithm used to generate an empirical horizon height. Ideally, an international horizon height database could be established that would rapidly merge data from various spacecraft to provide timely corrections that could be used by all.
The physical size of the sound horizon at recombination is a powerful source of information for early-time measurements of the Hubble constant H 0 , and many proposed solutions to the Hubble tension therefore involve modifications to this scale. In light of this, there has been growing interest in measuring H 0 independently of the sound horizon. We present the first such measurement to use data from the Dark Energy Spectroscopic Instrument (DESI), jointly analyzing the full-shape galaxy power spectra of DESI luminous red galaxies, emission line galaxies, quasars, and the bright galaxy sample, in a total of six redshift bins. Information from the sound horizon scale is removed from our constraints via a rescaling procedure at the power spectrum level, with our sound horizon-marginalized measurement being driven instead primarily by the matter-radiation equality scale. This measurement is then combined with additional sound horizon-free information from Planck+ACT CMB lensing, uncalibrated type Ia supernovae, and the DESI Lyman-α forest. We agnostically combine with the DESY5, Pantheon+, and Union3 supernova datasets, with our tightest respective constraints being H 0 = 66.7 +1.7 -1.9 , 67.9 +1.9 -2.1 , and 67.8 +2.0 -2.2 km s -1 Mpc -1 . This corresponds to a sub-3% sound horizon-free constraint of the Hubble constant, and is the most precise measurement of its kind to date. Even without including information from the sound horizon, our measurement is still in 2.2-3.0σ tension with SH0ES. Additionally, the consistency between our result and other measurements that do rely on the sound horizon scale provides no evidence for new early-Universe physics (e.g. early dark energy). Future DESI data releases will allow unprecedented measurements of H 0 and place strong constraints on models that use beyond-ΛCDM physics to ameliorate the Hubble tension.
Spacetime singularities pose a long-standing puzzle in quantum gravity. Unlike Schwarzschild, a generic family of black holes gives rise to a Cauchy horizon on which, even in the Hartle-Hawking state, quantum observables such as ⟨T μν ⟩ — the expectation value of the stress-energy tensor — can diverge, causing a breakdown of semiclassical gravity. Because they are diagnosed within quantum field theory (QFT) on a smooth background, these singularities may provide a better-controlled version of the spacetime singularity problem, and merit further study. Here, I highlight a mildness puzzle of Cauchy horizon singularities: the ⟨T μν ⟩ singularity is significantly milder than expected from symmetry and dimensional analysis. I address the puzzle in a simple spacetime ${\mathcal{W}}_P$, which arises universally near all black hole Cauchy horizons: the past of a codimension-two spacelike plane in flat spacetime. Specifically, I propose an extremely broad QFT construction in which, roughly speaking, Cauchy horizon singularities originate from operator insertions in the causal complement of the spacetime. The construction reproduces well-known outer horizon singularities (e.g., in the Boulware state), and remarkably, when applied to ${\mathcal{W}}_P$, gives rise to a universal mild singularity structure for robust singularities, ones whose leading singular behavior is state-independent. I make non-trivial predictions for all black hole Cauchy horizon singularities using this, and discuss extending the results beyond robust singularities and the strict near Cauchy horizon limit.
Abstract We generalize the formulation of horizon symmetries presented in previous literature to include diffeomorphisms that can shift the location of the horizon. In the context of the AdS/CFT duality, we show that horizon symmetries can be interpreted on the boundary as emergent low-energy gauge symmetries. In particular, we identify a new class of horizon symmetries that extend the so-called shift symmetry, which was previously postulated for effective field theories of maximally chaotic systems. Additionally, we comment on the connections of horizon symmetries with bulk calculations of out-of-time-ordered correlation functions and the phenomenon of pole-skipping.
The aerosol scattering coefficient as a function of height can be recovered from a direct inversion of the single-scattering horizon radiance provided the sun is above the horizon and an independent measurement of extinction as a function of height is made. Aerosol detection is effected by means of spacecraft measurements of the horizon radiance made during periods of spacecraft twilight. A solar occultation technique which allows the twilight measurements to be made when the sun is still above the horizon greatly reduces the complexity of the inversion problem. The second part of the paper reports on the use of a coronograph aboard Skylab to photograph the horizon just before spacecraft twilight in order to monitor the aerosol component above the tropopause. The coronograph picture, centered on 26.5 degrees E longitude and 63.0 degrees S latitude, shows that the aerosol layer peaks at a height of 48 plus or minus 1 km.
The work performed by the Attitude Determination and Control Section at the National Aeronautics and Space Administration/Goddard Space Flight Center in analyzing and evaluating the performance of infrared horizon sensors is presented. The results of studies performed during the 1960s are reviewed; several models for generating the Earth's infrared radiance profiles are presented; and the Horizon Radiance Modeling Utility, the software used to model the horizon sensor optics and electronics processing to computer radiance-dependent attitude errors, is briefly discussed. Also provided is mission experience from 12 spaceflight missions spanning the period from 1973 to 1984 and using a variety of horizon sensing hardware. Recommendations are presented for future directions for the infrared horizon sensing technology.
Recently substantial progress has been made towards design building and testifying remotely piloted Micro Air Vehicles (MAVs). This progress in overcoming the aerodynamic obstacles to flight at very small scales has, unfortunately, not been matched by similar progress in autonomous MAV flight. Thus, we propose a robust, vision-based horizon detection algorithm as the first step towards autonomous MAVs. In this paper, we first motivate the use of computer vision for the horizon detection task by examining the flight of birds (biological MAVs) and considering other practical factors. We then describe our vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification, over terrain that includes roads, buildings large and small, meadows, wooded areas, and a lake. We conclude with some sample horizon detection results and preview a companion paper, where the work discussed here forms the core of a complete autonomous flight stability system.
NASA's Orion Project has sparked a renewed interest in horizon-based optical navigation(OPNAV) techniques for spacecraft in the Earth-Moon system. Some approaches have begun to explore the geometry of horizon-based OPNAV and exploit the fact that it is a conic section problem. Therefore, the present paper focuses more deeply on understanding and leveraging the various geometric interpretations of horizon-based OPNAV. These results provide valuable insight into the fundamental workings of OPNAV solution methods, their convergence properties, and associated estimate covariance. Most importantly, the geometry and transformations uncovered in this paper lead to a simple and non-iterative solution to the generic horizon-based OPNAV problem. This represents a significant theoretical advancement over existing methods. Thus, we find that a clear understanding of geometric relationships is central to the prudent design, use, and operation of horizon-based OPNAV techniques.
Planetary rovers navigate in extreme environments for which a Global Positioning System (GPS) is unavailable, maps are restricted to relatively low resolution provided by orbital imagery, and compass information is often lacking due to weak or not existent magnetic fields. However, an accurate rover localization is particularly important to achieve the mission success by reaching the science targets, avoiding negative obstacles visible only in orbital maps, and maintaining good communication connections with ground. This paper describes a horizon solution for precise rover orientation estimation. The detected horizon in imagery provided by the on board navigation cameras is matched with the horizon rendered over the existing terrain model. The set of rotation parameters (roll, pitch yaw) that minimize the cost function between the two horizon curves corresponds to the rover estimated pose.
We present Jovian zonal wind speeds measured during the Cassini and New Horizons Jupiter flybys in 2000 and 2007, respectively. We performed our cloud tracking wind measurements using an automated, two-dimensional correlation imaging velocimetry technique. We analyzed all LORRI panchromatic images from the New Horizons Jupiter flyby dataset. This LORRI measurement documents the state of Jupiter’s zonal mean wind speed in 2007 and extends the historical record of Jupiter’s winds that serve as useful points of comparison for Juno observations. Among the Cassini ISS images, we analyzed the CL1CL2, CB2, UV3, BL1, BL2, GRN, RED, IR1, IR2, IR3, IR4, MT2, and MT3 filters. Our Cassini measurements provide valuable context to understand the altitudes probed by LORRI. Comparing the panchromatic LORRI measurements against past wind measurements using images captured with various narrow and wide-band camera filters is not straightforward. Because the Cassini ISS CL1CL2 “clear” filter’s performance is similar to that of LORRI, comparing CL1CL2 winds against LORRI results will help determine if the New Horizons measurements represent Jupiter’s cloud-top zonal wind speeds or if they are sensitive to different altitudes. In addition to placing our New Horizons measurements in altitudinal context, the Cassini ISS's IR4, IR2, RED, GRN, and BL1 filters are similar to those on Europa Clipper EIS camera. Wind measurements performed using those ISS filters will enable comparison to future missions, including anticipated observations to be taken by Europa Clipper.
We present Jovian zonal wind speeds measured during the Cassini and New Horizons Jupiter flybys in 2000 and 2007, respectively. We performed our cloud tracking wind measurements using an automated, two-dimensional correlation imaging velocimetry technique. We analyzed all LORRI panchromatic images from the New Horizons Jupiter flyby dataset. This LORRI measurement documents the state of Jupiter’s zonal mean wind speed in 2007 and extends the historical record of Jupiter’s winds. Among the Cassini ISS images, we processed the CL1CL2, CB2, UV3, BL1, BL2, GRN, RED, IR1, IR2, IR3, IR4, MT2, and MT3 filters. Our Cassini measurements provide valuable context to understand the altitudes probed by LORRI. Comparing the panchromatic LORRI measurements against past wind measurements using images captured with various narrow and wide-band camera filters is not straightforward. Because the Cassini ISS CL1CL2 “clear” filter’s performance is similar to that of LORRI, comparing CL1CL2 winds against LORRI results will help determine if the New Horizons measurements represent Jupiter’s cloud-top zonal wind speeds or if they are sensitive to different altitudes. In addition to placing our New Horizons measurements in altitudinal context, the Cassini ISS's IR4, IR2, RED, GRN, and BL1 filters are similar to those on Europa Clipper EIS camera. Wind measurements performed using those ISS filters will enable comparison to future missions, including anticipated observations to be taken by Europa Clipper
Accurate modeling of scrape-off layer (SOL) and divertor-edge dynamics is vital for designing plasma-facing components in fusion devices. High-fidelity edge fluid/neutral codes such as SOLPS-ITER capture SOL physics with high accuracy, but their computational cost limits broad parameter scans and long transient studies. We present transformer-based, autoregressive surrogates for efficient prediction of 2D, time-dependent plasma edge state fields. Trained on SOLPS-ITER spatiotemporal data for the KSTAR tokamak, the surrogates forecast electron temperature, electron density, and radiated power over extended horizons. We evaluate model variants trained with increasing autoregressive horizons (1–100 steps) on short- and long-horizon prediction tasks. Longer-horizon training systematically improves rollout stability and mitigates error accumulation, enabling stable predictions over hundreds to thousands of steps and reproducing key dynamical features such as the motion of high-radiation regions. Measured end-to-end wall-clock times show the surrogate is orders of magnitude faster than SOLPS-ITER, enabling rapid parameter exploration. Prediction accuracy degrades when the surrogate enters physical regimes not represented in the training dataset, motivating future work on data enrichment and physics-informed constraints. Overall, this approach provides a fast, accurate surrogate for computationally intensive plasma edge simulations, supporting rapid scenario exploration, control-oriented studies, and progress toward real-time applications in fusion devices.