Abstract We present a stellar dynamical mass measurement of a newly detected supermassive black hole (SMBH) at the center of the fast-rotating, massive elliptical galaxy NGC 2693 as part of the MASSIVE survey. We combine high signal-to-noise ratio integral field spectroscopy (IFS) from the Gemini Multi-Object Spectrograph with wide-field data from the Mitchell Spectrograph at McDonald Observatory to extract and model stellar kinematics of NGC 2693 from the central ∼150 pc out to ∼2.5 effective radii. Observations from Hubble Space Telescope WFC3 are used to determine the stellar light distribution. We perform fully triaxial Schwarzschild orbit modeling using the latest TriOS code and a Bayesian search in 6D galaxy model parameter space to determine NGC 2693's SMBH mass (MBH), stellar mass-to-light ratio, dark matter content, and intrinsic shape. We find and a triaxial intrinsic shape with axis ratiosp=b/a= 0.902 ± 0.009 and , triaxiality parameterT= 0.39 ± 0.04. In comparison, the best-fit orbit model in the axisymmetric limit and (cylindrical) Jeans anisotropic model of NGC 2693 prefer and , respectively. Neither model can account for the non-axisymmetric stellar velocity features present in the IFS data.
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A novel stochastic optimization method for handling misalignments of proton and photon doses in combined treatments
Abstract Objective.Combined proton–photon treatments, where most fractions are delivered with photons and only a few are delivered with protons, may represent a practical approach to optimally use limited proton resources. It has been shown that, when organs at risk (OARs) are located within or near the tumor, the optimal multi-modality treatment uses protons to hypofractionate parts of the target volume and photons to achieve near-uniform fractionation in dose-limiting healthy tissues, thus exploiting the fractionation effect. These plans may be sensitive to range and setup errors, especially misalignments between proton and photon doses. Thus, we developed a novel stochastic optimization method to directly incorporate these uncertainties into the biologically effective dose (BED)-based simultaneous optimization of proton and photon plans.Approach.The method considers the expected value and standard deviation of the cumulative BED in every voxel of a structure. For the target, a piecewise quadratic penalty function of the form is minimized, aiming for plans in which the expected BED minus two times the standard deviation exceeds the prescribed BED Analogously, is considered for OARs.Main results.Using a spinal metastasis case and a liver cancer patient, it is demonstrated that the novel stochastic optimization method yields robust combined treatment plans. Tumor coverage and a good sparing of the main OARs are maintained despite range and setup errors, and especially misalignments between proton and photon doses. This is achieved without explicitly considering all combinations of proton and photon error scenarios.Significance.Concerns about range and setup errors for safe clinical implementation of optimized proton–photon radiotherapy can be addressed through an appropriate stochastic planning method.
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- PAR ID:
- 10371467
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Physics in Medicine & Biology
- Volume:
- 67
- Issue:
- 18
- ISSN:
- 0031-9155
- Page Range / eLocation ID:
- Article No. 185006
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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