Paper |
Title |
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MOPOST054 |
A Hybrid Multi-Bend Achromat Lattice Design for SSRL-X |
207 |
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- J. Kim, X. Huang, P. Raimondi, J.A. Safranek, M. Song, K. Tian
SLAC, Menlo Park, California, USA
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We present a lattice design for SSRL-X which is a green-field low-emittance storage ring proposal. The lattice is based on the hybrid multi-bend achromat and has natural emittance of 63 pm with 24-cells periodicity and ~570 m circumference under 3.5 GeV energy. Modification on dedicated cells which lengthens straight sections but keeps the phase advance is explored to further reduce the natural emittance by inserting damping wigglers.
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DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2022-MOPOST054
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About • |
Received ※ 06 June 2022 — Revised ※ 14 June 2022 — Accepted ※ 15 June 2022 — Issue date ※ 09 July 2022 |
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TUPOMS036 |
Commissioning of the Lower Emittance Lattice at SPEAR3 |
1502 |
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- K. Tian, W.J. Corbett, S.M. Gierman, X. Huang, J. Kim, J.B. Langton, NL. Parry, J.A. Safranek, J.J. Sebek, M. Song, Z. Zhang
SLAC, Menlo Park, California, USA
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SPEAR3, commissioned in 2004, is a third generation light source at the SLAC National Accelerator Laboratory. The low emittance lattice with an emittance of 10 nm had been operated for over a decade until the recent commission of the new lower emittance lattice with 7 nm emittance. The new lattice, based on the same double-bend achromat lattice, has pushed toward the design limit of such type of lattice in SPEAR3. In this paper, we will elaborate our commissioning experience for the new lattice in SPEAR3.
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DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS036
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About • |
Received ※ 08 June 2022 — Revised ※ 12 June 2022 — Accepted ※ 13 June 2022 — Issue date ※ 29 June 2022 |
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TUPOMS037 |
RCDS-S: An Optimization Method to Compensate Accelerator Performance Drifts |
1506 |
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- Z. Zhang, X. Huang, M. Song
SLAC, Menlo Park, California, USA
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We propose an optimization algorithm, Safe Robust Conjugate Direction Search (RCDS-S), which can perform accelerator tuning while keeping the machine performance within a designated safe envelope. The algorithm builds probability models of the objective function using Lipschitz continuity of the function as well as characteristics of the drifts and applies to the selection of trial solutions to ensure the machine operates safely during tuning. The algorithm can run during normal user operation constantly, or periodically, to compensate for the performance drifts. Simulation and online tests have been done to validate the performance of the algorithm.
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DOI • |
reference for this paper
※ https://doi.org/10.18429/JACoW-IPAC2022-TUPOMS037
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|
About • |
Received ※ 08 June 2022 — Revised ※ 16 June 2022 — Accepted ※ 30 June 2022 — Issue date ※ 30 June 2022 |
Cite • |
reference for this paper using
※ BibTeX,
※ LaTeX,
※ Text/Word,
※ RIS,
※ EndNote (xml)
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