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Lewis L, Huang HY, Tran VT, Lehner S, Kueng R, Preskill J. Author Correction: Improved machine learning algorithm for predicting ground state properties. Nat Commun 2024; 15:1740. [PMID: 38409126 PMCID: PMC10897443 DOI: 10.1038/s41467-024-46164-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024] Open
Affiliation(s)
- Laura Lewis
- California Institute of Technology, Pasadena, CA, USA
- University of Cambridge, Cambridge, UK
| | - Hsin-Yuan Huang
- California Institute of Technology, Pasadena, CA, USA.
- Massachusetts Institute of Technology, Cambridge, MA, USA.
- Google Quantum AI, Venice, CA, USA.
| | | | | | | | - John Preskill
- California Institute of Technology, Pasadena, CA, USA
- AWS Center for Quantum Computing, Pasadena, CA, USA
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Lewis L, Huang HY, Tran VT, Lehner S, Kueng R, Preskill J. Improved machine learning algorithm for predicting ground state properties. Nat Commun 2024; 15:895. [PMID: 38291046 PMCID: PMC10828424 DOI: 10.1038/s41467-024-45014-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 01/08/2024] [Indexed: 02/01/2024] Open
Abstract
Finding the ground state of a quantum many-body system is a fundamental problem in quantum physics. In this work, we give a classical machine learning (ML) algorithm for predicting ground state properties with an inductive bias encoding geometric locality. The proposed ML model can efficiently predict ground state properties of an n-qubit gapped local Hamiltonian after learning from only [Formula: see text] data about other Hamiltonians in the same quantum phase of matter. This improves substantially upon previous results that require [Formula: see text] data for a large constant c. Furthermore, the training and prediction time of the proposed ML model scale as [Formula: see text] in the number of qubits n. Numerical experiments on physical systems with up to 45 qubits confirm the favorable scaling in predicting ground state properties using a small training dataset.
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Affiliation(s)
- Laura Lewis
- California Institute of Technology, Pasadena, CA, USA
- University of Cambridge, Cambridge, UK
| | - Hsin-Yuan Huang
- California Institute of Technology, Pasadena, CA, USA.
- Massachusetts Institute of Technology, Cambridge, MA, USA.
- Google Quantum AI, Venice, CA, USA.
| | | | | | | | - John Preskill
- California Institute of Technology, Pasadena, CA, USA
- AWS Center for Quantum Computing, Pasadena, CA, USA
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Abstract
Classical machine learning (ML) provides a potentially powerful approach to solving challenging quantum many-body problems in physics and chemistry. However, the advantages of ML over traditional methods have not been firmly established. In this work, we prove that classical ML algorithms can efficiently predict ground-state properties of gapped Hamiltonians after learning from other Hamiltonians in the same quantum phase of matter. By contrast, under a widely accepted conjecture, classical algorithms that do not learn from data cannot achieve the same guarantee. We also prove that classical ML algorithms can efficiently classify a wide range of quantum phases. Extensive numerical experiments corroborate our theoretical results in a variety of scenarios, including Rydberg atom systems, two-dimensional random Heisenberg models, symmetry-protected topological phases, and topologically ordered phases.
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Affiliation(s)
- Hsin-Yuan Huang
- Institute for Quantum Information and Matter and Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA
| | - Richard Kueng
- Institute for Integrated Circuits, Johannes Kepler University, Linz, Austria
| | | | - Victor V Albert
- Joint Center for Quantum Information and Computer Science, National Institute of Standards and Technology and University of Maryland, College Park, MD, USA
| | - John Preskill
- Institute for Quantum Information and Matter and Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA.,AWS Center for Quantum Computing, Pasadena, CA, USA
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Huang HY, Broughton M, Cotler J, Chen S, Li J, Mohseni M, Neven H, Babbush R, Kueng R, Preskill J, McClean JR. Quantum advantage in learning from experiments. Science 2022; 376:1182-1186. [PMID: 35679419 DOI: 10.1126/science.abn7293] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Quantum technology promises to revolutionize how we learn about the physical world. An experiment that processes quantum data with a quantum computer could have substantial advantages over conventional experiments in which quantum states are measured and outcomes are processed with a classical computer. We proved that quantum machines could learn from exponentially fewer experiments than the number required by conventional experiments. This exponential advantage is shown for predicting properties of physical systems, performing quantum principal component analysis, and learning about physical dynamics. Furthermore, the quantum resources needed for achieving an exponential advantage are quite modest in some cases. Conducting experiments with 40 superconducting qubits and 1300 quantum gates, we demonstrated that a substantial quantum advantage is possible with today's quantum processors.
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Affiliation(s)
- Hsin-Yuan Huang
- Institute for Quantum Information and Matter, Caltech, Pasadena, CA, USA.,Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA
| | | | - Jordan Cotler
- Harvard Society of Fellows, Cambridge, MA 02138, USA.,Black Hole Initiative, Cambridge, MA 02138, USA
| | - Sitan Chen
- Department of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA, USA.,Simons Institute for the Theory of Computing, Berkeley, CA, USA
| | - Jerry Li
- Microsoft Research AI, Redmond, WA 98052, USA
| | | | | | | | - Richard Kueng
- Institute for Integrated Circuits, Johannes Kepler University Linz, Austria
| | - John Preskill
- Institute for Quantum Information and Matter, Caltech, Pasadena, CA, USA.,Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA.,AWS Center for Quantum Computing, Pasadena, CA 91125, USA
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Huang HY, Kueng R, Preskill J. Efficient Estimation of Pauli Observables by Derandomization. Phys Rev Lett 2021; 127:030503. [PMID: 34328776 DOI: 10.1103/physrevlett.127.030503] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/14/2021] [Indexed: 06/13/2023]
Abstract
We consider the problem of jointly estimating expectation values of many Pauli observables, a crucial subroutine in variational quantum algorithms. Starting with randomized measurements, we propose an efficient derandomization procedure that iteratively replaces random single-qubit measurements by fixed Pauli measurements; the resulting deterministic measurement procedure is guaranteed to perform at least as well as the randomized one. In particular, for estimating any L low-weight Pauli observables, a deterministic measurement on only of order log(L) copies of a quantum state suffices. In some cases, for example, when some of the Pauli observables have high weight, the derandomized procedure is substantially better than the randomized one. Specifically, numerical experiments highlight the advantages of our derandomized protocol over various previous methods for estimating the ground-state energies of small molecules.
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Affiliation(s)
- Hsin-Yuan Huang
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
| | - Richard Kueng
- Institute for Integrated Circuits, Johannes Kepler University Linz, A-4040, Austria
| | - John Preskill
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
- Walter Burke Institute for Theoretical Physics, Caltech, Pasadena, California 91125, USA
- AWS Center for Quantum Computing, Pasadena, California 91125, USA
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Huang HY, Kueng R, Preskill J. Information-Theoretic Bounds on Quantum Advantage in Machine Learning. Phys Rev Lett 2021; 126:190505. [PMID: 34047595 DOI: 10.1103/physrevlett.126.190505] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/17/2021] [Accepted: 04/02/2021] [Indexed: 06/12/2023]
Abstract
We study the performance of classical and quantum machine learning (ML) models in predicting outcomes of physical experiments. The experiments depend on an input parameter x and involve execution of a (possibly unknown) quantum process E. Our figure of merit is the number of runs of E required to achieve a desired prediction performance. We consider classical ML models that perform a measurement and record the classical outcome after each run of E, and quantum ML models that can access E coherently to acquire quantum data; the classical or quantum data are then used to predict the outcomes of future experiments. We prove that for any input distribution D(x), a classical ML model can provide accurate predictions on average by accessing E a number of times comparable to the optimal quantum ML model. In contrast, for achieving an accurate prediction on all inputs, we prove that the exponential quantum advantage is possible. For example, to predict the expectations of all Pauli observables in an n-qubit system ρ, classical ML models require 2^{Ω(n)} copies of ρ, but we present a quantum ML model using only O(n) copies. Our results clarify where the quantum advantage is possible and highlight the potential for classical ML models to address challenging quantum problems in physics and chemistry.
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Affiliation(s)
- Hsin-Yuan Huang
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
| | - Richard Kueng
- Institute for Integrated Circuits, Johannes Kepler University Linz, Linz 4040, Austria
| | - John Preskill
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
- Walter Burke Institute for Theoretical Physics, Caltech, Pasadena, California 91125, USA
- AWS Center for Quantum Computing, Pasadena, California 91125, USA
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Kueng R, Mueller S, Loebner HA, Frei D, Volken W, Aebersold DM, Stampanoni MFM, Fix MK, Manser P. TriB-RT: Simultaneous optimization of photon, electron and proton beams. Phys Med Biol 2021; 66:045006. [PMID: 32413883 DOI: 10.1088/1361-6560/ab936f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
PURPOSE To develop a novel treatment planning process (TPP) with simultaneous optimization of modulated photon, electron and proton beams for improved treatment plan quality in radiotherapy. METHODS A framework for fluence map optimization of Monte Carlo (MC) calculated beamlet dose distributions is developed to generate treatment plans consisting of photon, electron and spot scanning proton fields. Initially, in-house intensity modulated proton therapy (IMPT) plans are compared to proton plans created by a commercial treatment planning system (TPS). A triple beam radiotherapy (TriB-RT) plan is generated for an exemplary academic case and the dose contributions of the three particle types are investigated. To investigate the dosimetric potential, a TriB-RT plan is compared to an in-house IMPT plan for two clinically motivated cases. Benefits of TriB-RT for a fixed proton beam line with a single proton field are investigated. RESULTS In-house optimized IMPT are of at least equal or better quality than TPS-generated proton plans, and MC-based optimization shows dosimetric advantages for inhomogeneous situations. Concerning TriB-RT, for the academic case, the resulting plan shows substantial contribution of all particle types. For the clinically motivated case, improved sparing of organs at risk close to the target volume is achieved compared to IMPT (e.g. myelon and brainstem [Formula: see text] -37%) at cost of an increased low dose bath (healthy tissue V 10% +22%). In the scenario of a fixed proton beam line, TriB-RT plans are able to compensate the loss in degrees of freedom to substantially improve plan quality compared to a single field proton plan. CONCLUSION A novel TPP which simultaneously optimizes photon, electron and proton beams was successfully developed. TriB-RT shows the potential for improved treatment plan quality and is especially promising for cost-effective single-room proton solutions with a fixed beamline in combination with a conventional linac delivering photon and electron fields.
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Affiliation(s)
- R Kueng
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Bern, Switzerland
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Elben A, Kueng R, Huang HYR, van Bijnen R, Kokail C, Dalmonte M, Calabrese P, Kraus B, Preskill J, Zoller P, Vermersch B. Mixed-State Entanglement from Local Randomized Measurements. Phys Rev Lett 2020; 125:200501. [PMID: 33258654 DOI: 10.1103/physrevlett.125.200501] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 10/20/2020] [Indexed: 06/12/2023]
Abstract
We propose a method for detecting bipartite entanglement in a many-body mixed state based on estimating moments of the partially transposed density matrix. The estimates are obtained by performing local random measurements on the state, followed by postprocessing using the classical shadows framework. Our method can be applied to any quantum system with single-qubit control. We provide a detailed analysis of the required number of experimental runs, and demonstrate the protocol using existing experimental data [Brydges et al., Science 364, 260 (2019)SCIEAS0036-807510.1126/science.aau4963].
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Affiliation(s)
- Andreas Elben
- Center for Quantum Physics, University of Innsbruck, Innsbruck A-6020, Austria
- Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck A-6020, Austria
| | - Richard Kueng
- Institute for Integrated Circuits, Johannes Kepler University Linz, Altenbergerstrasse 69, 4040 Linz, Austria
| | - Hsin-Yuan Robert Huang
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
| | - Rick van Bijnen
- Center for Quantum Physics, University of Innsbruck, Innsbruck A-6020, Austria
- Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck A-6020, Austria
| | - Christian Kokail
- Center for Quantum Physics, University of Innsbruck, Innsbruck A-6020, Austria
- Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck A-6020, Austria
| | - Marcello Dalmonte
- The Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34151 Trieste, Italy
- SISSA, via Bonomea 265, 34136 Trieste, Italy
| | - Pasquale Calabrese
- The Abdus Salam International Center for Theoretical Physics, Strada Costiera 11, 34151 Trieste, Italy
- SISSA, via Bonomea 265, 34136 Trieste, Italy
- INFN, via Bonomea 265, 34136 Trieste, Italy
| | - Barbara Kraus
- Institute for Theoretical Physics, University of Innsbruck, A6020 Innsbruck, Austria
| | - John Preskill
- Institute for Quantum Information and Matter, Caltech, Pasadena, California 91125, USA
- Department of Computing and Mathematical Sciences, Caltech, Pasadena, California 91125, USA
- Walter Burke Institute for Theoretical Physics, Caltech, Pasadena, California 91125, USA
- AWS Center for Quantum Computing, Pasadena, California 91125, USA
| | - Peter Zoller
- Center for Quantum Physics, University of Innsbruck, Innsbruck A-6020, Austria
- Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck A-6020, Austria
| | - Benoît Vermersch
- Center for Quantum Physics, University of Innsbruck, Innsbruck A-6020, Austria
- Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences, Innsbruck A-6020, Austria
- Université Grenoble Alpes, CNRS, LPMMC, 38000 Grenoble, France
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Kueng R, Guyer G, Volken W, Frei D, Stabel F, Stampanoni MFM, Manser P, Fix MK. Development of an extended Macro Monte Carlo method for efficient and accurate dose calculation in magnetic fields. Med Phys 2020; 47:6519-6530. [PMID: 33075168 DOI: 10.1002/mp.14542] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 09/18/2020] [Accepted: 09/28/2020] [Indexed: 11/06/2022] Open
Abstract
MOTIVATION Progress in the field of magnetic resonance (MR)-guided radiotherapy has triggered the need for fast and accurate dose calculation in presence of magnetic fields. The aim of this work is to satisfy this need by extending the macro Monte Carlo (MMC) method to enable dose calculation for photon, electron, and proton beams in a magnetic field. METHODS The MMC method is based on the transport of particles in macroscopic steps through an absorber by sampling the relevant physical quantities from a precalculated database containing probability distribution functions. To enable MMC particle transport in a magnetic field, a transformation accounting for the Lorentz force is applied for each macro step by rotating the sampled position and direction around the magnetic field vector. The transformed position and direction distributions on local geometries are validated against full MC for electron and proton pencil beams. To enable photon dose calculation, an in-house MC algorithm is used for photon transport and interaction. Emerging secondary charged particles are passed to MMC for transport and energy deposition. The extended MMC dose calculation accuracy and efficiency is assessed by comparison with EGSnrc (photon and electron beams) and Geant4 (proton beam) calculated dose distributions of different energies and homogeneous magnetic fields for broad beams impinging on water phantoms with bone and lung inhomogeneities. RESULTS The geometric transformation on the local geometries is able to reproduce the results of full MC for all investigated settings (difference in mean value and standard deviation <1%). Macro Monte Carlo calculated dose distributions in a homogeneous magnetic field are in agreement with EGSnrc and Geant4, respectively, with gamma passing rates >99.6% (global 2%, 2 mm and 10% threshold criteria) for all situations. MMC achieves a substantial efficiency gain of up to a factor of 21 (photon beam), 66 (electron beam), and 356 (proton beam) compared to EGSnrc or Geant4. CONCLUSION Efficient and accurate dose calculation in magnetic fields was successfully enabled by utilizing the developed extended MMC transport method for photon, electron, and proton beams.
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Affiliation(s)
- R Kueng
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - G Guyer
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - W Volken
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - D Frei
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - F Stabel
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - M F M Stampanoni
- Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH), Zurich, Switzerland
| | - P Manser
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - M K Fix
- Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Kueng R, Oborn B, Roberts N, Causer T, Stampanoni M, Manser P, Keall P, Fix M. Towards MR-guided electron therapy: Measurement and simulation of clinical electron beams in magnetic fields. Phys Med 2020; 78:83-92. [DOI: 10.1016/j.ejmp.2020.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 08/17/2020] [Accepted: 09/01/2020] [Indexed: 10/23/2022] Open
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Roth I, Kueng R, Kimmel S, Liu YK, Gross D, Eisert J, Kliesch M. Recovering Quantum Gates from Few Average Gate Fidelities. Phys Rev Lett 2018; 121:170502. [PMID: 30411921 PMCID: PMC6768554 DOI: 10.1103/physrevlett.121.170502] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2018] [Indexed: 05/30/2023]
Abstract
Characterizing quantum processes is a key task in the development of quantum technologies, especially at the noisy intermediate scale of today's devices. One method for characterizing processes is randomized benchmarking, which is robust against state preparation and measurement errors and can be used to benchmark Clifford gates. Compressed sensing techniques achieve full tomography of quantum channels essentially at optimal resource efficiency. In this Letter, we show that the favorable features of both approaches can be combined. For characterizing multiqubit unitary gates, we provide a rigorously guaranteed and practical reconstruction method that works with an essentially optimal number of average gate fidelities measured with respect to random Clifford unitaries. Moreover, for general unital quantum channels, we provide an explicit expansion into a unitary 2-design, allowing for a practical and guaranteed reconstruction also in that case. As a side result, we obtain a new statistical interpretation of the unitarity-a figure of merit characterizing the coherence of a process.
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Affiliation(s)
- I. Roth
- Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, Germany
| | - R. Kueng
- Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, USA
| | - S. Kimmel
- Department of Computer Science, Middlebury College, USA
| | - Y.-K. Liu
- National Institute of Standards and Technology, Gaithersburg, USA
- Joint Center for Quantum Information and Computer Science (QuICS), University of Maryland, College Park, USA
| | - D. Gross
- Institute for Theoretical Physics, University of Cologne, Germany
| | - J. Eisert
- Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, Germany
| | - M. Kliesch
- Institute of Theoretical Physics and Astrophysics, National Quantum Information Centre, University of Gdańsk, Poland
- Institute for Theoretical Physics, Heinrich Heine University Düsseldorf, Germany
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Mueller S, Manser P, Volken W, Frei D, Kueng R, Herrmann E, Elicin O, Aebersold DM, Stampanoni MFM, Fix MK. Part 2: Dynamic mixed beam radiotherapy (DYMBER): Photon dynamic trajectories combined with modulated electron beams. Med Phys 2018; 45:4213-4226. [PMID: 29992574 DOI: 10.1002/mp.13085] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 06/27/2018] [Accepted: 06/28/2018] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The purpose of this study was to develop a treatment technique for dynamic mixed beam radiotherapy (DYMBER) utilizing increased degrees of freedom (DoF) of a conventional treatment unit including different particle types (photons and electrons), intensity and energy modulation and dynamic gantry, table, and collimator rotations. METHODS A treatment planning process has been developed to create DYMBER plans combining photon dynamic trajectories (DTs) and step and shoot electron apertures collimated with the photon multileaf collimator (pMLC). A gantry-table path is determined for the photon DTs with minimized overlap of the organs at risk (OARs) with the target. In addition, an associated dynamic collimator rotation is established with minimized area between the pMLC leaves and the target contour. pMLC sequences of photon DTs and electron pMLC apertures are then simultaneously optimized using direct aperture optimization (DAO). Subsequently, the final dose distribution of the electron pMLC apertures is calculated using the Swiss Monte Carlo Plan (SMCP). The pMLC sequences of the photon DTs are then re-optimized with a finer control point resolution and with the final electron dose distribution taken into account. Afterwards, the final photon dose distribution is calculated also using the SMCP and summed together with the one of the electrons. This process is applied for a brain and two head and neck cases. The resulting DYMBER dose distributions are compared to those of dynamic trajectory radiotherapy (DTRT) plans consisting only of photon DTs and clinically applied VMAT plans. Furthermore, the deliverability of the DYMBER plans is verified in terms of dosimetric accuracy, delivery time and collision avoidance. For this purpose, The DYMBER plans are delivered to Gafchromic EBT3 films placed in an anthropomorphic head phantom on a Varian TrueBeam linear accelerator. RESULTS For each case, the dose homogeneity in the target is similar or better for DYMBER compared to DTRT and VMAT. Averaged over all three cases, the mean dose to the parallel OARs is 16% and 28% lower, D2% to the serial OARs is 17% and 37% lower and V10% to normal tissue is 12% and 4% lower for the DYMBER plans compared to the DTRT and VMAT plans, respectively. The DYMBER plans are delivered without collision and with a 4-5 min longer delivery time than the VMAT plans. The absolute dose measurements are compared to calculation by gamma analysis using 2% (global)/2 mm criteria with passing rates of at least 99%. CONCLUSIONS A treatment technique for DYMBER has been successfully developed and verified for its deliverability. The dosimetric superiority of DYMBER over DTRT and VMAT indicates utilizing increased DoF to be the key to improve brain and head and neck radiation treatments in future.
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Affiliation(s)
- S Mueller
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - P Manser
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - W Volken
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - D Frei
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - R Kueng
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - E Herrmann
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - O Elicin
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - D M Aebersold
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
| | - M F M Stampanoni
- Institute for Biomedical Engineering, ETH Zürich and PSI, CH-5232, Villigen, Switzerland
| | - M K Fix
- Division of Medical Radiation Physics, Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, CH-3010, Bern, Switzerland
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Mueller S, Fix MK, Joosten A, Henzen D, Frei D, Volken W, Kueng R, Aebersold DM, Stampanoni MFM, Manser P. Simultaneous optimization of photons and electrons for mixed beam radiotherapy. ACTA ACUST UNITED AC 2017; 62:5840-5860. [DOI: 10.1088/1361-6560/aa70c5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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Kueng R, Driscoll B, Manser P, Fix MK, Stampanoni M, Keller H. Quantification of local image noise variation in PET images for standardization of noise-dependent analysis metrics. Biomed Phys Eng Express 2017. [DOI: 10.1088/2057-1976/3/2/025007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Abstract
Achieving error rates that meet or exceed the fault-tolerance threshold is a central goal for quantum computing experiments, and measuring these error rates using randomized benchmarking is now routine. However, direct comparison between measured error rates and thresholds is complicated by the fact that benchmarking estimates average error rates while thresholds reflect worst-case behavior when a gate is used as part of a large computation. These two measures of error can differ by orders of magnitude in the regime of interest. Here we facilitate comparison between the experimentally accessible average error rates and the worst-case quantities that arise in current threshold theorems by deriving relations between the two for a variety of physical noise sources. Our results indicate that it is coherent errors that lead to an enormous mismatch between average and worst case, and we quantify how well these errors must be controlled to ensure fair comparison between average error probabilities and fault-tolerance thresholds.
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Affiliation(s)
- Richard Kueng
- Centre for Engineered Quantum Systems, School of Physics, University of Sydney, Sydney, 2006 New South Wales, Australia
- Institute for Theoretical Physics, University of Cologne, D-50937 Cologne, Germany
- Institute for Physics and FDM, University of Freiburg, D-79104 Freiburg, Germany
| | - David M Long
- Centre for Engineered Quantum Systems, School of Physics, University of Sydney, Sydney, 2006 New South Wales, Australia
| | - Andrew C Doherty
- Centre for Engineered Quantum Systems, School of Physics, University of Sydney, Sydney, 2006 New South Wales, Australia
| | - Steven T Flammia
- Centre for Engineered Quantum Systems, School of Physics, University of Sydney, Sydney, 2006 New South Wales, Australia
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Kueng R, Manser P, Fix MK, Driscoll B, Stampanoni MFM, Keller H. SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia. Med Phys 2016. [DOI: 10.1118/1.4957108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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18
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Keller H, Kueng R, Shek T, Driscoll B, Yeung I, Milosevic M, Jaffray D. WE-H-207A-06: Hypoxia Quantification in Static PET Images: The Signal in the Noise. Med Phys 2016. [DOI: 10.1118/1.4958011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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19
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Chaves R, Kueng R, Brask JB, Gross D. Unifying framework for relaxations of the causal assumptions in Bell's theorem. Phys Rev Lett 2015; 114:140403. [PMID: 25910096 DOI: 10.1103/physrevlett.114.140403] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Indexed: 06/04/2023]
Abstract
Bell's theorem shows that quantum mechanical correlations can violate the constraints that the causal structure of certain experiments impose on any classical explanation. It is thus natural to ask to which degree the causal assumptions-e.g., locality or measurement independence-have to be relaxed in order to allow for a classical description of such experiments. Here we develop a conceptual and computational framework for treating this problem. We employ the language of Bayesian networks to systematically construct alternative causal structures and bound the degree of relaxation using quantitative measures that originate from the mathematical theory of causality. The main technical insight is that the resulting problems can often be expressed as computationally tractable linear programs. We demonstrate the versatility of the framework by applying it to a variety of scenarios, ranging from relaxations of the measurement independence, locality, and bilocality assumptions, to a novel causal interpretation of Clauser-Horne-Shimony-Holt inequality violations.
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Affiliation(s)
- R Chaves
- Institute for Physics, University of Freiburg, Rheinstrasse 10, D-79104 Freiburg, Germany
| | - R Kueng
- Institute for Physics, University of Freiburg, Rheinstrasse 10, D-79104 Freiburg, Germany
| | - J B Brask
- Département de Physique Théorique, Université de Genève, 1211 Genève, Switzerland
| | - D Gross
- Institute for Physics, University of Freiburg, Rheinstrasse 10, D-79104 Freiburg, Germany
- Freiburg Center for Data Analysis and Modeling, Eckerstrasse 1, 79104 Freiburg, Germany
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