{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T00:26:17Z","timestamp":1723595177612},"reference-count":32,"publisher":"Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften","license":[{"start":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:00:00Z","timestamp":1723507200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["quantum-journal.org"],"crossmark-restriction":false},"short-container-title":["Quantum"],"abstract":"<jats:p>Assessment of practical quantum information processing (QIP) remains partial without understanding limits imposed by noise. Unfortunately, mere description of noise grows exponentially with system size, becoming cumbersome even for modest sized systems of imminent practical interest. We fulfill the need for estimates on performing noisy quantum state preparation, verification, and observation. To do the estimation we propose fast numerical algorithms to maximize the expectation value of any <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>d<\/mml:mi><\/mml:math>-dimensional observable over states of bounded purity. This bound on purity factors in noise in a measurable way. Our fastest algorithm takes <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>O<\/mml:mi><mml:mo stretchy=\"false\">(<\/mml:mo><mml:mi>d<\/mml:mi><mml:mo stretchy=\"false\">)<\/mml:mo><\/mml:math> steps if the eigendecomposition of the observable is known, otherwise takes <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><mml:mi>O<\/mml:mi><mml:mo stretchy=\"false\">(<\/mml:mo><mml:msup><mml:mi>d<\/mml:mi><mml:mn>3<\/mml:mn><\/mml:msup><mml:mo stretchy=\"false\">)<\/mml:mo><\/mml:math> steps at worst. The algorithms also solve maximum likelihood estimation for quantum state tomography with convex and even non-convex purity constraints. Numerics show performance of our key sub-routine (it finds in linear time a probability vector with bounded norm that most overlaps with a fixed vector) can be several orders of magnitude faster than a common state-of-the-art convex optimization solver. Our work fosters a practical way forward to asses limitations on QIP imposed by quantum noise. Along the way, we also give a simple but fundamental insight, noisy systems (equivalently noisy Hamiltonians) always give higher ground-state energy than their noiseless counterparts.<\/jats:p>","DOI":"10.22331\/q-2024-08-13-1437","type":"journal-article","created":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T12:24:26Z","timestamp":1723551866000},"page":"1437","update-policy":"http:\/\/dx.doi.org\/10.22331\/q-crossmark-policy-page","source":"Crossref","is-referenced-by-count":0,"title":["Maximum expectation of observables with restricted purity states"],"prefix":"10.22331","volume":"8","author":[{"given":"Vikesh","family":"Siddhu","sequence":"first","affiliation":[{"name":"IBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA"},{"name":"IBM Quantum, IBM Research India"}]},{"given":"John Aaron","family":"Smolin","sequence":"additional","affiliation":[{"name":"IBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY, USA"}]}],"member":"9598","published-online":{"date-parts":[[2024,8,13]]},"reference":[{"key":"0","doi-asserted-by":"publisher","unstructured":"H. J. Briegel, D. E. Browne, W. D\u00fcr, R. Raussendorf, and M. Van den Nest, ``Measurement-based quantum computation&apos;&apos; 5, 19-26 (2009).","DOI":"10.1038\/nphys1157"},{"key":"1","unstructured":"Daniel Gottesman ``Stabilizer Codes and Quantum Error Correction&apos;&apos; (1997)."},{"key":"2","doi-asserted-by":"publisher","unstructured":"Peter W. Shor ``Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer&apos;&apos; SIAM Journal on Computing 26, 1484\u20131509 (1997).","DOI":"10.1137\/s0097539795293172"},{"key":"3","doi-asserted-by":"publisher","unstructured":"Vikesh Siddhuand John Smolin ``Optimal one-shot entanglement sharing&apos;&apos; Phys. Rev. A 108, 032617 (2023).","DOI":"10.1103\/PhysRevA.108.032617"},{"key":"4","doi-asserted-by":"publisher","unstructured":"A. I. Lvovskyand M. G. Raymer ``Continuous-variable optical quantum-state tomography&apos;&apos; Rev. Mod. Phys. 81, 299\u2013332 (2009).","DOI":"10.1103\/RevModPhys.81.299"},{"key":"5","doi-asserted-by":"publisher","unstructured":"Yong Siah Teo ``Introduction to Quantum-State Estimation&apos;&apos; World Scientific (2015).","DOI":"10.1142\/9617"},{"key":"6","doi-asserted-by":"publisher","unstructured":"Sam McArdle, Suguru Endo, Al\u00e1n Aspuru-Guzik, Simon C. Benjamin, and Xiao Yuan, ``Quantum computational chemistry&apos;&apos; Rev. Mod. Phys. 92, 015003 (2020).","DOI":"10.1103\/RevModPhys.92.015003"},{"key":"7","doi-asserted-by":"publisher","unstructured":"I. M. Georgescu, S. Ashhab, and Franco Nori, ``Quantum simulation&apos;&apos; Rev. Mod. Phys. 86, 153\u2013185 (2014).","DOI":"10.1103\/RevModPhys.86.153"},{"key":"8","doi-asserted-by":"publisher","unstructured":"A S Holevoand V Giovannetti ``Quantum channels and their entropic characteristics&apos;&apos; Reports on Progress in Physics 75, 046001 (2012).","DOI":"10.1088\/0034-4885\/75\/4\/046001"},{"key":"9","unstructured":"Michael M. Wolf ``Quantum Channels and Operations - Guided Tour&apos;&apos; Lecture notes Lecture notes (2012)."},{"key":"10","doi-asserted-by":"publisher","unstructured":"M. Mohseni, A. T. Rezakhani, and D. A. Lidar, ``Quantum-process tomography: Resource analysis of different strategies&apos;&apos; Phys. Rev. A 77, 032322 (2008).","DOI":"10.1103\/PhysRevA.77.032322"},{"key":"11","doi-asserted-by":"publisher","unstructured":"John Preskill ``Quantum Computing in the NISQ era and beyond&apos;&apos; Quantum 2, 79 (2018).","DOI":"10.22331\/q-2018-08-06-79"},{"key":"12","doi-asserted-by":"crossref","unstructured":"Adriano Barenco, Andre` Berthiaume, David Deutsch, Artur Ekert, Richard Jozsa, and Chiara Macchiavello, ``Stabilisation of Quantum Computations by Symmetrisation&apos;&apos; (1996).","DOI":"10.1137\/S0097539796302452"},{"key":"13","doi-asserted-by":"publisher","unstructured":"Harry Buhrman, Richard Cleve, and Wim van Dam, ``Quantum Entanglement and Communication Complexity&apos;&apos; SIAM Journal on Computing 30, 1829\u20131841 (2001).","DOI":"10.1137\/S0097539797324886"},{"key":"14","doi-asserted-by":"publisher","unstructured":"Ken Xuan Wei, Emily Pritchett, David M. Zajac, David C. McKay, and Seth Merkel, ``Characterizing non-Markovian Off-Resonant Errors in Quantum Gates&apos;&apos; (2023).","DOI":"10.1103\/PhysRevApplied.21.024018"},{"key":"15","doi-asserted-by":"publisher","unstructured":"Suvrit Sra, Sebastian Nowozin, and Stephen J. Wright, ``Optimization for Machine Learning&apos;&apos; The MIT Press (2011).","DOI":"10.7551\/mitpress\/8996.001.0001"},{"key":"16","unstructured":"Martin Andersen, Joachim Dahl, and Lieven Vandenberghe, ``CVXOPT: Convex Optimization&apos;&apos; (2021)."},{"key":"17","doi-asserted-by":"publisher","unstructured":"John Watrous ``The Theory of Quantum Information&apos;&apos; Cambridge University Press (2018).","DOI":"10.1017\/9781316848142"},{"key":"18","doi-asserted-by":"publisher","unstructured":"Rajarshi Paland Somshubhro Bandyopadhyay ``Entanglement sharing via qudit channels: Nonmaximally entangled states may be necessary for one-shot optimal singlet fraction and negativity&apos;&apos; Physical Review A 97, 032322 (2018).","DOI":"10.1103\/PhysRevA.97.032322"},{"key":"19","doi-asserted-by":"publisher","unstructured":"Rajarshi Pal, Somshubhro Bandyopadhyay, and Sibasish Ghosh, ``Entanglement sharing through noisy qubit channels: One-shot optimal singlet fraction&apos;&apos; Physical Review A 90, 052304 (2014).","DOI":"10.1103\/PhysRevA.90.052304"},{"key":"20","unstructured":"Frank Verstraeteand Henri Verschelde ``On quantum channels&apos;&apos; (2003)."},{"key":"21","doi-asserted-by":"publisher","unstructured":"Stephen P. Boydand Lieven Vandenberghe ``Convex optimization&apos;&apos; Cambridge University Press (2004).","DOI":"10.1017\/CBO9780511804441"},{"key":"22","doi-asserted-by":"publisher","unstructured":"John A. Smolin, Jay M. Gambetta, and Graeme Smith, ``Efficient Method for Computing the Maximum-Likelihood Quantum State from Measurements with Additive Gaussian Noise&apos;&apos; Phys. Rev. Lett. 108, 070502 (2012).","DOI":"10.1103\/PhysRevLett.108.070502"},{"key":"23","doi-asserted-by":"publisher","unstructured":"Victor Y. Panand Zhao Q. Chen ``The complexity of the matrix eigenproblem&apos;&apos; Proceedings of the thirty-first annual ACM symposium on Theory of Computing 507\u2013516 (1999).","DOI":"10.1145\/301250.301389"},{"key":"24","doi-asserted-by":"publisher","unstructured":"James Demmel, Ioana Dumitriu, and Olga Holtz, ``Fast linear algebra is stable&apos;&apos; Numerische Mathematik 108, 59\u201391 (2007) arXiv:math\/0612264.","DOI":"10.1007\/s00211-007-0114-x"},{"key":"25","doi-asserted-by":"publisher","unstructured":"Rajendra Bhatia ``Matrix Analysis&apos;&apos; Springer New York (1997).","DOI":"10.1007\/978-1-4612-0653-8"},{"key":"26","unstructured":"William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery, ``Numerical Recipes in C (2Nd Ed.): The Art of Scientific Computing&apos;&apos; Cambridge University Press (1992)."},{"key":"27","doi-asserted-by":"publisher","unstructured":"Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, St\u00e9fan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C J Carey, \u0130lhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Ant\u00f4nio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors, ``SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python&apos;&apos; Nature Methods 17, 261\u2013272 (2020).","DOI":"10.1038\/s41592-019-0686-2"},{"key":"28","doi-asserted-by":"publisher","unstructured":"Guillaume Sagnoland Maximilian Stahlberg ``PICOS: A Python interface to conic optimization solvers&apos;&apos; Journal of Open Source Software 7, 3915 (2022).","DOI":"10.21105\/joss.03915"},{"key":"29","doi-asserted-by":"publisher","unstructured":"Robin Blume-Kohout ``Hedged Maximum Likelihood Quantum State Estimation&apos;&apos; Phys. Rev. Lett. 105, 200504 (2010).","DOI":"10.1103\/PhysRevLett.105.200504"},{"key":"30","doi-asserted-by":"publisher","unstructured":"Yong Siah Teo, Huangjun Zhu, Berthold-Georg Englert, Jaroslav \u0158eh\u00e1\u010dek, and Zden\u011bk Hradil, ``Quantum-State Reconstruction by Maximizing Likelihood and Entropy&apos;&apos; Phys. Rev. Lett. 107, 020404 (2011).","DOI":"10.1103\/PhysRevLett.107.020404"},{"key":"31","doi-asserted-by":"publisher","unstructured":"Vikesh Siddhu ``Maximum a posteriori probability estimates for quantum tomography&apos;&apos; Physical Review A 99, 012342 (2019).","DOI":"10.1103\/PhysRevA.99.012342"}],"container-title":["Quantum"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/quantum-journal.org\/papers\/q-2024-08-13-1437\/pdf\/","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T12:24:32Z","timestamp":1723551872000},"score":1,"resource":{"primary":{"URL":"https:\/\/quantum-journal.org\/papers\/q-2024-08-13-1437\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,13]]},"references-count":32,"URL":"https:\/\/doi.org\/10.22331\/q-2024-08-13-1437","archive":["CLOCKSS"],"relation":{},"ISSN":["2521-327X"],"issn-type":[{"value":"2521-327X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,13]]},"article-number":"1437"}}