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1. Conceptual design and modeling of particle-matter interaction cooling systems for muon based applications

Author

Diktys Stratakis, H. Kamal Sayed, Chris T. Rogers, Androula Alekou, and Jaroslaw Pasternak

Subjects
Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

An ionization cooling channel is a tightly spaced lattice containing absorbers for reducing the momentum of the muon beam, rf cavities for restoring the longitudinal momentum, and strong solenoids for focusing. Such a lattice can be an essential feature for fundamental high-energy physics applications. In this paper we design, simulate, and compare four individual cooling schemes that rely on ionization cooling. We establish a scaling characterizing the impact of rf gradient limitations on the overall performance and systematically compare important lattice parameters such as the required magnetic fields and the number of cavities and absorber lengths for each cooling scenario. We discuss approaches for reducing the peak magnetic field inside the rf cavities by either increasing the lattice cell length or adopting a novel bucked-coil configuration. We numerically examine the performance of our proposed channels with two independent codes that fully incorporate all basic particle-matter-interaction physical processes.

Published
2014
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3. A storage ring experiment to detect a proton electric dipole moment

Author

D. Kawall, Kyoko Makino, S. T. Park, Eric M. Metodiev, M. Bai, Andreas Lehrach, M. Grosse-Perdekamp, P. Fierlinger, A. Pesce, D. Moricciani, W. Meng, J. Talman, T. Roser, Andrew Ivanov, A.U. Luccio, Richard Talman, G. Venanzoni, M. Incagli, G. Guidoboni, J. Benante, Francois Méot, Konstantin Zioutas, Wolfram Fischer, Y. Giomataris, G. Fanourakis, Vadim Ptitsyn, S. Rescia, A. Sidorin, Jason Crnkovic, B. King, Michael Syphers, Selcuk Haciomeroglu, Richard Baartman, N. Tsoupas, B. I. Khazin, Yannis K. Semertzidis, Martin Berz, Yong-Ho Lee, Y. Senichev, G. Zavattini, Kevin Brown, J. Pretz, V. Tishchenko, T. J. V. Bowcock, S. K. Nayak, E. J. Stephenson, Ivan Koop, W.W. MacKay, Yuri F. Orlov, Alexey Lyapin, B. C. K. Casey, M. Blaskiewicz, C. Touramanis, A. N. Zelenski, R. Maier, M. Conte, Valeri Lebedev, G. Hoffstaetter, S. Baessler, E. Won, C. S. Özben, K. Vetter, Frank Rathmann, A. V. Fedotov, D. Raparia, A. Stahl, H. Huang, P. Pile, M. J. Lee, M. Gaisser, Shyh Yuan Lee, William J. Marciano, William Morse, B. Podobedov, D. M. Lazarus, P. Levi Sandri, Rasmus Larsen, Alexander J. Silenko, H. Kamal Sayed, Serge Andrianov, L. Miceli, N. Malitsky, P. Lenisa, Nikolaos Simos, H. Stroeher, S. Nagaitsev, S. Vlassis, Vassilis Anastassopoulos, E. J. Ramberg, Y. I. Kim, and V. Polychronakos

Subjects
Systematic error, Accelerator Physics (physics.acc-ph), Proton, Physics beyond the Standard Model, FOS: Physical sciences, p: electric moment, momentum, 01 natural sciences, High Energy Physics - Experiment, NO, Nuclear physics, Polarisation, Storage Rings, Fundamental Symmetries, Physics beyond Standard Model, High Energy Physics - Experiment (hep-ex), 0103 physical sciences, ddc:530, 010306 general physics, Instrumentation, Fundamental Symmetries, Polarisation, Physics, polarization, 010308 nuclear & particles physics, new physics, Magic (programming), Physics beyond Standard Model, storage ring, sensitivity, Electric dipole moment, electric moment [p], Storage Rings, Physics - Accelerator Physics, Storage ring, dipole, experimental results
Abstract

A new experiment is described to detect a permanent electric dipole moment of the proton with a sensitivity of $10^{-29}e\cdot$cm by using polarized "magic" momentum $0.7$~GeV/c protons in an all-electric storage ring. Systematic errors relevant to the experiment are discussed and techniques to address them are presented. The measurement is sensitive to new physics beyond the Standard Model at the scale of 3000~TeV., Comment: 8 pages, 3 figures

Published
2016
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4. The Measurement of the Anomalous Magnetic Moment of the Muon at Fermilab

Author

R. Chislett, J. Carroll, D. Cauz, Andrew Smith, M. Lee, A. Anastasi, E. Hazen, M. Eads, G. Pauletta, R. Osofsky, B. Quinn, R. Fatemi, I. Logashenko, S. Baessler, D.A. Sweigart, N. A. Kuchinskiy, M. W. Smith, D. Still, Yannis K. Semertzidis, W. Gohn, K. L. Giovanetti, V. Tishchenko, L. Welty-Rieger, R. Di Stefano, C. Fu, M. Iacovacci, E. Barzi, V. Volnykh, J. F. Ostiguy, D. W. Hertzog, T. Stuttard, V. A. Baranov, C. J. G. Onderwater, Michael Syphers, G. Luo, V. P. Druzhinin, E. Won, P. T. Debevec, C. Yoshikawa, J. Grange, Martin Fertl, Stephen Maxfield, F. Azfar, A. Epps, L Li, P. Winter, C. Johnstone, A. Fioretti, B. Drendel, K. T. Pitts, M R M Warren, L. K. Gibbons, D. Stöckinger, M. Whitley, Donald B. Rubin, M. Rominsky, J. Crnkovic, T. P. Gorringe, T. Walton, C. Ferrari, Z. Meadows, G. Venanzoni, Thomas Teubner, Nicholas A. Pohlman, S. Haciomeroglu, M. Gaisser, M. Wormald, B. Casey, Frederick Gray, H. Freidsam, Marin Karuza, K. R. Lynch, P. Kammel, S. Henry, S.B. Dabagov, A. L. Lyon, C. Schlesier, E. Motuk, Yuri F. Orlov, D. Allspach, N. Rider, T. J. V. Bowcock, B. Abi, N. Kinnaird, D. Babusci, A. Para, R. M. Carey, A. de Gouvea, J. Johnstone, J. P. Miller, S. Lee, A.T. Fienberg, G. Di Sciascio, Y. Kim, H. Schellman, L.P. Alonzi, H Yang, H. Kamal Sayed, B. L. Roberts, Edward J. Swanson, V. N. Duginov, E. Ramberg, E. Frlez, N. S. Froemming, I. Kourbanis, J. Mott, L. Santi, D. Kawall, Giovanni Cantatore, N. V. Khomutov, G. Corradi, D. Flay, C. C. Polly, Nicholas Eggert, S. Marignetti, R. Bjorkquist, S. Kim, Benjamin T. King, D. Moricciani, C. Gabbanini, A. Tewlsey-Booth, V. Krylov, Yu. M. Shatunov, Andre Frankenthal, S. Leo, M. E. Convery, S. Mastroianni, A. Chapelain, A. Palladino, Andrzej Wolski, H. Nguyen, B. Kiburg, Alexander Mikhailichenko, K. W. Merritt, J. Kaspar, Dinko Pocanic, M. Popovic, M. Lancaster, W. M. Morse, Timothy Chupp, M. McEvoy, Dariush Hampai, X. Ji, M. Shenk, S. Al-Kilani, A. K. Soha, D. A. Tarazona, Klaus-Peter Jungmann, Alejandro Garcia, Logashenko, I., Grange, J., Winter, P., Carey, R. M., Hazen, E., Kinnaird, N., Miller, J. P., Mott, J., Roberts, B. L., Crnkovic, J., Morse, W. M., Sayed, H. Kamal, Tishchenko, V., Druzhinin, V. P., Shatunov, Y. M., Bjorkquist, R., Chapelain, A., Eggert, N., Frankenthal, A., Gibbons, L., Kim, S., Mikhailichenko, A., Orlov, Y., Rider, N., Rubin, D., Sweigart, D., Allspach, D., Barzi, E., Casey, B., Convery, M. E., Drendel, B., Freidsam, H., Johnstone, C., Johnstone, J., Kiburg, B., Kourbanis, I., Lyon, A. L., Merritt, K. W., Morgan, J. P., Nguyen, H., Ostiguy, J. F., Para, A., Polly, C. C., Popovic, M., Ramberg, E., Rominsky, M., Soha, A. K., Still, D., Walton, T., Yoshikawa, C., Jungmann, K., Onderwater, C. J. G., Debevec, P., Leo, S., Pitts, K., Schlesier, C., Anastasi, A., Babusci, D., Corradi, G., Hampai, D., Palladino, A., Venanzoni, G., Dabagov, S., Ferrari, C., Fioretti, A., Gabbanini, C., Di Stefano, R., Marignetti, S., Iacovacci, M., Mastroianni, S., Di Sciascio, G., Moricciani, D., Cantatore, Giovanni, Karuza, M., Giovanetti, K., Baranov, V., Duginov, V., Khomutov, N., Krylov, V., Kuchinskiy, N., Volnykh, V., Gaisser, M., Haciomeroglu, S., Kim, Y., Lee, S., Lee, M., Semertzidis, Y. K., Won, E., Fatemi, R., Gohn, W., Gorringe, T., Bowcock, T., Carroll, J., King, B., Maxfield, S., Smith, A., Teubner, T., Whitley, M., Wormald, M., Wolski, A., Al Kilani, S., Chislett, R., Lancaster, M., Motuk, E., Stuttard, T., Warren, M., Flay, D., Kawall, D., Meadows, Z., Syphers, M., Tarazona, D., Chupp, T., Tewlsey Booth, A., Quinn, B., Eads, M., Epps, A., Luo, G., Mcevoy, M., Pohlman, N., Shenk, M., de Gouvea, A., Welty Rieger, L., Schellman, H., Abi, B., Azfar, F., Henry, S., Gray, F., Fu, C., Ji, X., Li, L., Yang, H., Stockinger, D., Cauz, D., Pauletta, G., Santi, L., Baessler, S., Frlez, E., Pocanic, D., Alonzi, L. P., Fertl, M., Fienberg, A., Froemming, N., Garcia, A., Hertzog, D. W., Kammel, P., Kaspar, J., Osofsky, R., Smith, M., Swanson, E., Lynch, K., Precision Frontier, Ostiguy, J. -F., Cantatore, G., Al-Kilani, S., Tewlsey-Booth, A., Welty-Rieger, L., and Abys, Salvatore

Subjects
Particle physics, magnetic moment, standard model, General Physics and Astronomy, Standard deviation, Standard Model, Muon magnetic moment, Nuclear physics, Physics and Astronomy (all), anomalous magnetic moment, Positron, muon anomaly, muon, Fermilab, Physical and Theoretical Chemistry, instrumentation, Physics, Muon, Anomalous magnetic moment, Standard model, Chemistry (all), Anomalous magnetic dipole moment, Magnetic moment, General Chemistry, Magnetic field, High Energy Physics::Experiment, measurement, muon, magnetic moment, instrumentation, measurement
Abstract

The anomalous magnetic moment of the muon is one of the most precisely measured quantities in experimental particle physics. Its latest measurement at Brookhaven National Laboratory deviates from the Standard Model expectation by approximately 3.5 standard deviations. The goal of the new experiment, E989, now under construction at Fermilab, is a fourfold improvement in precision. Here, we discuss the details of the future measurement and its current status. C 2015 AIP Publishing LLC. [http://dx.doi.org/10.1063/1.4917553]

Published
2015

5. The New Muon g-2 experiment at Fermilab

Author

B. Abi T. Albahri, S. Al-Kilani, D. Allspach, L. P. Alonzi, A. Anastasi, F. Azfar, D. Babusci, S. Baessler, V. A. Baranov, E. Barzi, R. Bjorkquist, T. Bowcock, G. Cantatore, R. M. Carey, J. Carroll, B. Casey, D. Cauz, A. Chapelain, S. Chappa, S. Chattopadhyay, R. Chislett, T. E. Chupp, M. Convery, G. Corradi, J. Crnkovic, S. Dabagov, P. T. Debevec, G. Di Sciascio, R. Di Stefano, B. Drendel, V. P. Druzhinin, V. N. Duginov, M. Eads, N. Eggert, A. Epps, R. Fatemi, C. Ferrari, M. Fertl, A. T. Fienberg, A. Fioretti, D. Flay, A. S. Frankenthal, H. Friedsam, E. Frlez, N. S. Froemming, C. Fu, C. Gabbanini, M. Gaisser, S. Ganguly, A. Garcia, J. George, L. K. Gibbons, K. L. Giovanetti, S. Goadhouse, W. Gohn, T. Gorringe, J. Grange, F. Gray, S. Haciomeroglu, T. Halewood-Leagas, D. Hampai, E. Hazen, S. Henry, D. W. Hertzog, J. L. Holzbauer, M. Iacovacci, C. Johnstone, J. A. Johnstone, K. Jungmann, H. Kamal Sayed, P. Kammel, M. Karuza, J. Kaspar, D. Kawall, L. Kelton, K. S. Khaw, N. V. Khomutov, B. Kiburg, S. C. Kim, Y. I. Kim, B. King, N. Kinnaird, I. A. Koop, I. Kourbanis, V. A. Krylov, A. Kuchibhotla, N. A. Kuchinskiy, M. Lancaster, M. J. Lee, S. Lee, S. Leo, L. Li, I. Logashenko, G. Luo, K. R. Lynch, A. Lyon, S. Marignetti, S. Mastroianni, S. Maxfield, M. McEvoy, Z. Meadows, W. Merritt, A. A. Mikhailichenko, J. P. Miller, J. P. Morgan, D. Moricciani, W. M. Morse, J. Mott, E. Motuk, H. Nguyen, Y. Orlov, R. Osofsky, J. -F. Ostiguy, A. Palladino, G. Pauletta, K. Pitts, D. Pocanic, N. Pohlman, C. Polly, J. Price, B. Quinn, N. Raha, E. Ramberg, N. T. Rider, J. L. Ritchie, B. L. Roberts, M. Rominsky, D. L. Rubin, L. Santi, C. Schlesier, Y. K. Semertzidis, Y. M. Shatunov, M. Shenk, A. Smith, M. W. Smith, A. Soha, E. Solodov, D. Still, D. Stöckinger, T. Stuttard, H. E. Swanson, D. A. Sweigart, M. J. Syphers, S. Szustkowski, D. Tarazona, T. Teubner, A. E. Tewlsey-Booth, V. Tishchenko, G. Venanzoni, V. P. Volnykh, T. Walton, M. Warren, L. Welty-Rieger, M. Whitley, P. Winter, A. Wolski, E. Won, M. Wormald, W. Wu, H. Yang, C. Yoshikawa, Albahri, B. Abi T., Al-Kilani, S., Allspach, D., Alonzi, L. P., Anastasi, A., Azfar, F., Babusci, D., Baessler, S., Baranov, V. A., Barzi, E., Bjorkquist, R., Bowcock, T., Cantatore, G., Carey, R. M., Carroll, J., Casey, B., Cauz, D., Chapelain, A., Chappa, S., Chattopadhyay, S., Chislett, R., Chupp, T. E., Convery, M., Corradi, G., Crnkovic, J., Dabagov, S., Debevec, P. T., Di Sciascio, G., Di Stefano, R., Drendel, B., Druzhinin, V. P., Duginov, V. N., Eads, M., Eggert, N., Epps, A., Fatemi, R., Ferrari, C., Fertl, M., Fienberg, A. T., Fioretti, A., Flay, D., Frankenthal, A. S., Friedsam, H., Frlez, E., Froemming, N. S., Fu, C., Gabbanini, C., Gaisser, M., Ganguly, S., Garcia, A., George, J., Gibbons, L. K., Giovanetti, K. L., Goadhouse, S., Gohn, W., Gorringe, T., Grange, J., Gray, F., Haciomeroglu, S., Halewood-Leagas, T., Hampai, D., Hazen, E., Henry, S., Hertzog, D. W., Holzbauer, J. L., Iacovacci, M., Johnstone, C., Johnstone, J. A., Jungmann, K., Kamal Sayed, H., Kammel, P., Karuza, M., Kaspar, J., Kawall, D., Kelton, L., Khaw, K. S., Khomutov, N. V., Kiburg, B., Kim, S. C., Kim, Y. I., King, B., Kinnaird, N., Koop, I. A., Kourbanis, I., Krylov, V. A., Kuchibhotla, A., Kuchinskiy, N. A., Lancaster, M., Lee, M. J., Lee, S., Leo, S., Li, L., Logashenko, I., Luo, G., Lynch, K. R., Lyon, A., Marignetti, S., Mastroianni, S., Maxfield, S., Mcevoy, M., Meadows, Z., Merritt, W., Mikhailichenko, A. A., Miller, J. P., Morgan, J. P., Moricciani, D., Morse, W. M., Mott, J., Motuk, E., Nguyen, H., Orlov, Y., Osofsky, R., Ostiguy, J. -F., Palladino, A., Pauletta, G., Pitts, K., Pocanic, D., Pohlman, N., Polly, C., Price, J., Quinn, B., Raha, N., Ramberg, E., Rider, N. T., Ritchie, J. L., Roberts, B. L., Rominsky, M., Rubin, D. L., Santi, L., Schlesier, C., Semertzidis, Y. K., Shatunov, Y. M., Shenk, M., Smith, A., Smith, M. W., Soha, A., Solodov, E., Still, D., Stöckinger, D., Stuttard, T., Swanson, H. E., Sweigart, D. A., Syphers, M. J., Szustkowski, S., Tarazona, D., Teubner, T., Tewlsey-Booth, A. E., Tishchenko, V., Venanzoni, G., Volnykh, V. P., Walton, T., Warren, M., Welty-Rieger, L., Whitley, M., Winter, P., Wolski, A., Won, E., Wormald, M., Wu, W., Yang, H., and Yoshikawa, C.

Subjects
Precision Physics, Muon magnetic anomaly, Muon g-2 experiment
Abstract

There is a long standing discrepancy between the Standard Model prediction for the muon and the value measured by the Brookhaven E821 Experiment. At present the discrepancy stands at about three standard deviations, with a comparable accuracy between experiment and theory. Two new proposals – at Fermilab and J-PARC – plan to improve the experimental uncertainty by a factor of 4, and it is expected that there will be a significant reduction in the uncertainty of the Standard Model prediction. I will review the status of the planned experiment at Fermilab, E989, which will analyse 21 times more muons than the BNL experiment and discuss how the systematic uncertainty will be reduced by a factor of 3 such that a precision of 0.14 ppm can be achieved.

Published
2015

6. A Pareto-based beam orientation optimization method for spot scanning intensity-modulated proton therapy.

Author

Kamal Sayed H, Herman MG, and Beltran CJ

Subjects
Brain Neoplasms radiotherapy, Humans, Organs at Risk radiation effects, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted methods, Radiotherapy, Intensity-Modulated adverse effects
Abstract

Purpose: To provide a proof of principle of a Pareto-based method to automatically generate optimal intensity-modulated proton therapy (IMPT) plans for various noncoplanar beam orientations., Methods: A novel multicriteria beam orientation optimization (MCBOO) method was developed to generate Pareto database of optimal plans. The MCBOO method automatically explores the beam orientations and the scalarization parameters of the IMPT plans simultaneously. The MCBOO method is based on multicriteria bilevel optimization (i.e., hierarchical optimization with two nested levels, named the upper and lower level optimization). In MCBOO, the upper level optimization explores the noncoplanar beam orientation space, while the lower level explores the scalarization parameters for a given beam orientation. Differential evolution method was used in both levels, and the Pareto optimal plans were aggregated from the bilevel optimizations to construct the Pareto database. The MCBOO method was implemented on a multinode multi-GPU cluster, and it was tested on three brain tumor patient cases. The Pareto database of the three patients was generated for a set of DVH-based objectives. A statistical analysis was performed between a selected set of MCBOO plans and the manual plan (plan with manually selected beam orientation based on the clinical experience and optimized with the same single plan iterative optimizer used in the MCBOO). The selected set of MCBOO plans consisted of plans that matched the performance of the manual plan [i.e., MCBOO plans that have the same target coverage (within 2%) as the manual plan or better and achieved the same dose (within 2%) or lower to all of the organs at risks (OARs) but one OAR]. Additionally, a dosimetric comparison between of one of the selected MCBOO plans vs the manual plan was conducted., Results: The multicriteria beam orientation optimization algorithm automatically generated Pareto plans for the three noncoplanar brain tumor cases. The MCBOO plans provided an alternative objective trade-offs to the manual plan. The selected MCBOO plans showed a reduction in dose to multiple organs at risk vs the manual plan with a maximum value which ranged between 10.8 and 12.9 Gy for the three patients. The trade-off of the OAR dose reduction resulted in higher dose to no more than one OAR for each of the selected MCBOO plans vs the manual plan. The maximum dose increase in the MCBOO plans over the manual plan ranged from 7.8 to 11.8 Gy., Conclusions: A novel multicriteria beam orientation optimization method was developed and tested on three IMPT patient cases. The method automatically generates Pareto plans database by exploring the noncoplanar beam orientations. The method was able to identify beam orientations with Pareto optimal plans that are comparable to the manually created plans with varying objective trade-offs., (© 2020 American Association of Physicists in Medicine.)

Published
2020
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7. Adaptive method for multicriteria optimization of intensity-modulated proton therapy.

Author

Kamal-Sayed H, Ma J, Tseung H, Abdel-Rehim A, Herman MG, and Beltran CJ

Subjects
Algorithms, Child, Head and Neck Neoplasms radiotherapy, Humans, Orbital Neoplasms radiotherapy, Radiotherapy Planning, Computer-Assisted, Proton Therapy methods, Radiotherapy, Intensity-Modulated methods
Abstract

Purpose: Provide an adaptive multicriteria optimization (MCO) method for intensity-modulated proton therapy (IMPT) utilizing GPU technology. Previously described limitations of MCO such as Pareto approximation and limitation on the number of objectives were addressed., Methods: The treatment planning process for IMPT must account for multiple objectives, which requires extensive treatment planning resources. Often a large number of objectives (>10) are required. Hence the need for an MCO algorithm that can handle large number of objectives. The novelty of the MCO method presented here lies on the introduction of the adaptive weighting scheme that can generate a well-distributed and dense representation of the Pareto surface for a large number of objectives in an efficient manner. In our approach the generated Pareto surface is constructed for a set of DVH objectives. The MCO algorithm is based on the augmented weighted Chebychev metric (AWCM) method with an adaptive weighting scheme. This scheme uses the differential evolution (DE) method to generate a set of well-distributed Pareto points. The quality of the Pareto points' distribution in the objective space was assessed quantitatively using the Pareto sampling metric. The MCO algorithm was developed to perform multiple parallel searches to achieve a rapid mapping of the Pareto surface, produce clinically deliverable plans, and was implemented on a GPU cluster. The MCO algorithm was tested on two clinical cases with 10 and 18 objectives. For each case one of the MCO-generated plans was selected for comparison with the clinically generated plan. The MCO plan was randomly selected out of the set of MCO plans that had target coverage similar to the clinically generated plan and the same or better sparing of the organs at risk (OAR). Additionally, a validation study of the AWCM method vs the weighted sum method was performed., Results: The adaptive MCO algorithm generated Pareto points on the Pareto hypersurface in a fast (2-3 hr) and efficient manner for 2 cases with 10 and 18 objectives. The MCO algorithm generated a dense and well-distributed set of Pareto points on the objective space, and was able to achieve minimization of the Pareto sampling metric. The selected MCO plan showed an improvement of the DVH objectives in comparison to the clinically optimized plan in both cases. For case one, the MCO plan showed a 48% reduction of the 50% dose to OARs and a 16% reduction of the 1% dose to OARs. For case 2, the MCO plan showed a 72% reduction of the 50% dose to OARs and a 42% reduction of the 1% dose to OARs. The comparison of AWCM to WS showed that the AWCM method has a dosimetric advantage over WS for both patient cases., Conclusion: We introduced an adaptive MCO algorithm for IMPT accelerated using GPUs. The algorithm is based on an adaptive method for generating Pareto plans in the objective space. We have shown that the algorithm can provide rapid and efficient mapping of the multicriteria Pareto surface with clinically deliverable plans., (© 2018 American Association of Physicists in Medicine.)

Published
2018
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8. A storage ring experiment to detect a proton electric dipole moment.

Author

Anastassopoulos V, Andrianov S, Baartman R, Baessler S, Bai M, Benante J, Berz M, Blaskiewicz M, Bowcock T, Brown K, Casey B, Conte M, Crnkovic JD, D'Imperio N, Fanourakis G, Fedotov A, Fierlinger P, Fischer W, Gaisser MO, Giomataris Y, Grosse-Perdekamp M, Guidoboni G, Hacıömeroğlu S, Hoffstaetter G, Huang H, Incagli M, Ivanov A, Kawall D, Kim YI, King B, Koop IA, Lazarus DM, Lebedev V, Lee MJ, Lee S, Lee YH, Lehrach A, Lenisa P, Levi Sandri P, Luccio AU, Lyapin A, MacKay W, Maier R, Makino K, Malitsky N, Marciano WJ, Meng W, Meot F, Metodiev EM, Miceli L, Moricciani D, Morse WM, Nagaitsev S, Nayak SK, Orlov YF, Ozben CS, Park ST, Pesce A, Petrakou E, Pile P, Podobedov B, Polychronakos V, Pretz J, Ptitsyn V, Ramberg E, Raparia D, Rathmann F, Rescia S, Roser T, Kamal Sayed H, Semertzidis YK, Senichev Y, Sidorin A, Silenko A, Simos N, Stahl A, Stephenson EJ, Ströher H, Syphers MJ, Talman J, Talman RM, Tishchenko V, Touramanis C, Tsoupas N, Venanzoni G, Vetter K, Vlassis S, Won E, Zavattini G, Zelenski A, and Zioutas K

Abstract

A new experiment is described to detect a permanent electric dipole moment of the proton with a sensitivity of 10 -29 e ⋅ cm by using polarized "magic" momentum 0.7 GeV/c protons in an all-electric storage ring. Systematic errors relevant to the experiment are discussed and techniques to address them are presented. The measurement is sensitive to new physics beyond the standard model at the scale of 3000 TeV.

Published
2016
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