- Open Access
Fighting Exponentially Small Gaps by Counterdiabatic Driving
PRX Quantum 7, 010322 – Published 2 February, 2026
DOI: https://doi.org/10.1103/tgzt-dy3h
Abstract
We investigate the efficiency of approximate counterdiabatic driving (CD) in accelerating adiabatic passage through exponentially small gaps. First, we analyze a minimal spin-glass bottleneck model that is analytically tractable and exhibits both an exponentially small gap at the transition point and a change in the ground state that involves a macroscopic rearrangement of spins. Using the variational Floquet-Krylov expansion to construct CD terms, we find that while the formation of excitations is significantly suppressed, achieving a fully adiabatic evolution remains challenging. Extending our investigation to realistic NP-hard spin-glass problems—specifically, the 3-regular Max Cut and 3-xorsat—we find again that local CD expansions lead to negligible improvements in the final ground-state fidelity. These results highlight the limited impact of local CD methods in overcoming the bottlenecks associated with first-order quantum phase transitions. To address this limitation, we propose an alternative method, termed quantum brachistochrone counterdiabatic driving (QBCD), which employs the approximate full CD connecting the ground state and the first-excited state at a single-parameter value close to the critical point. In the minimal spin-glass model, QBCD enables exponentially faster adiabatic evolution than the local strategies. To alleviate the challenges of its experimental and classical implementation for realistic np-hard problems, we exponentially reduce the nonlocality of the QBCD Hamiltonian by sparsifying its matrix elements to the density of the local expansions. Despite this drastic simplification, sparsified QBCD maintains finite ground-state fidelity at driving times exponentially shorter than in local strategies and counterdiabatic optimized local driving, demonstrating that even an exponentially reduced fraction of nonlocality near the critical point is sufficient to achieve significant speedup across spin-glass bottlenecks. At the same time, reduced nonlocality facilitates classical implementations via advanced numerical methods, while on quantum hardware its truncation serves as a resource-efficient approximation scheme for higher-order CD realizations.
Physics Subject Headings (PhySH)
Popular Summary
The control of quantum systems via adiabatic processes lies at the heart of current quantum technological developments. Of particular interest are control schemes speeding up adiabatic dynamics across first-order quantum phase transitions. In these scenarios, the adiabatic dynamics can only be maintained by slowing down exponentially with the system size due to the presence of avoided level crossings with exponentially small gaps between macroscopically distinct states. The effect is typically present in models with disorder, such as spin-glass systems encoding combinatorial optimization problems. A successful framework for engineering additional control terms, and accelerating the adiabatic dynamics, is counterdiabatic driving (CD). However, to apply this powerful analytical method to many-body systems such that it can be subsequently realized on real quantum devices, it is necessary to perform some approximations and truncate the nonlocal operators required by the exact theory.
Our work examines how efficiently approximate CD can accelerate the adiabatic passage through the difficult first-order quantum phase transitions in a generic spin-glass bottleneck. We find that while approximate CD can reduce excitation formation during time evolution, it struggles to achieve full adiabatic evolution due to the presence of a small gap. To overcome the problem, we suggest an alternative approach, termed quantum brachistochrone counterdiabatic driving (QBCD). The main idea is to tackle directly the critical point relying solely on the approximate knowledge of the ground state and the first-excited state at a single value of the control parameter. We find that QBCD significantly improves accuracy in reaching the target quantum state, offering a better solution for optimization problems like NP-hard Ising models where local CD strategies fall short.
Article Text
References (123)
- A. P. Young, S. Knysh, and V. N. Smelyanskiy, Size dependence of the minimum excitation gap in the quantum adiabatic algorithm, Phys. Rev. Lett. 101, 170503 (2008); First-order phase transition in the quantum adiabatic algorithm, Phys. Rev. Lett. 104, 020502 (2010).
- M. H. S. Amin, Effect of local minima on adiabatic quantum optimization, Phys. Rev. Lett. 100, 130503 (2008).
- M. H. S. Amin and V. Choi, First-order quantum phase transition in adiabatic quantum computation, Phys. Rev. A 80, 062326 (2009).
- B. Altshuler, H. Krovi, and J. Roland, Adiabatic quantum optimization fails for random instances of NP-complete problems, arXiv:0908.2782; Anderson localization makes adiabatic quantum optimization fail, Proc. Natl. Acad. Sci. USA 107, 12446 (2010).
- K.-P. Marzlin and B. C. Sanders, Inconsistency in the application of the adiabatic theorem, Phys. Rev. Lett. 93, 160408 (2004).
- S. Jansen, M.-B. Ruskai, and R. Seiler, Bounds for the adiabatic approximation with applications to quantum computation, J. Math. Phys. 48, 102111 (2007).
- C. R. Laumann, R. Moessner, A. Scardicchio, and S. L. Sondhi, Quantum annealing: The fastest route to quantum computation? Eur. Phys. J. Spec. Top. 224, 75 (2015).
- S. Knysh and V. Smelyanskiy, On the relevance of avoided crossings away from quantum critical point to the complexity of quantum adiabatic algorithm, arXiv:1005.3011.
- L. Foini, G. Semerjian, and F. Zamponi, Solvable model of quantum random optimization problems, Phys. Rev. Lett. 105, 167204 (2010).
- T. Jörg, F. Krzakala, J. Kurchan, and A. C. Maggs, Simple glass models and their quantum annealing, Phys. Rev. Lett. 101, 147204 (2008).
- T. Jörg, F. Krzakala, G. Semerjian, and F. Zamponi, First-order transitions and the performance of quantum algorithms in random optimization problems, Phys. Rev. Lett. 104, 207206 (2010).
- S. Bachmann, W. De Roeck, and M. Fraas, Adiabatic theorem for quantum spin systems, Phys. Rev. Lett. 119, 060201 (2017).
- S. Bachmann, W. De Roeck, and M. Fraas, The adiabatic theorem and linear response theory for extended quantum systems, Commun. Math. Phys. 361, 997 (2018).
- M. B. Hastings, Locality in quantum and Markov dynamics on lattices and networks, Phys. Rev. Lett. 93, 140402 (2004); Quasi-adiabatic continuation in gapped spin and fermion systems: Goldstone’s theorem and flux periodicity, J. Stat. Mech.: Theory Exp. 2007, P05010 (2007); in Quantum Theory from Small to Large Scales: Lecture Notes of the Les Houches Summer School: Volume 95, August 2010 (Oxford University, Oxford, 2012); Quasi-adiabatic continuation for disordered systems: Applications to correlations, Lieb-Schultz-Mattis, and Hall conductance, arXiv:1001.5280.
- M. B. Hastings and X.-G. Wen, Quasiadiabatic continuation of quantum states: The stability of topological ground-state degeneracy and emergent gauge invariance, Phys. Rev. B 72, 045141 (2005).
- M. B. Hastings and S. Michalakis, Quantization of Hall conductance for interacting electrons on a torus, Commun. Math. Phys. 334, 433 (2015).
- W. De Roeck and M. Schütz, Local perturbations perturb–exponentially–locally, J. Math. Phys. 56, 061901 (2015).
- E. Farhi, J. Goldston, D. Gosset, S. Gutmann, H. B. Meyer, and P. Shor, Quantum adiabatic algorithms, small gaps, and different paths, Quantum Inf. Comput. 11, 181 (2011).
- V. Choi, Avoid first order quantum phase transition by changing problem Hamiltonians, arXiv:1010.1220; Different adiabatic quantum optimization algorithms for the NP-complete exact cover and 3SAT problems, arXiv:1010.1221; Different adiabatic quantum optimization algorithms for the NP-complete exact cover problem, Proc. Natl. Acad. Sci. U.S.A. 108, E19 (2011)..
- N. G. Dickson, Elimination of perturbative crossings in adiabatic quantum optimization, New J. Phys. 13, 073011 (2011).
- N. G. Dickson and M. H. S. Amin, Does adiabatic quantum optimization fail for NP-complete problems? Phys. Rev. Lett. 106, 050502 (2011).
- V. Choi, The effects of the problem Hamiltonian parameters on the minimum spectral gap in adiabatic quantum optimization, Quantum Inf. Process. 19, 90 (2020).
- S. Suzuki, H. Nishimori, and M. Suzuki, Quantum annealing of the random-field Ising model by transverse ferromagnetic interactions, Phys. Rev. E 75, 051112 (2007).
- Y. Seki and H. Nishimori, Quantum annealing with antiferromagnetic fluctuations, Phys. Rev. E 85, 051112 (2012).
- B. Seoane and H. Nishimori, Many-body transverse interactions in the quantum annealing of the p-spin ferromagnet, J. Phys. A 45, 435301 (2012).
- R. D. Somma and S. Boixo, Spectral gap amplification, SIAM J. Comp. 42, 593 (2013).
- E. Crosson, E. Farhi, C. Y.-Y. Lin, H.-H. Lin, and P. Shor, Different strategies for optimization using the quantum adiabatic algorithm, arXiv:1401.7320.
- L. Hormozi, E. W. Brown, G. Carleo, and M. Troyer, Nonstoquastic Hamiltonians and quantum annealing of an Ising spin glass, Phys. Rev. B 95, 184416 (2017).
- Y. Susa, Y. Yamashiro, M. Yamamoto, and H. Nishimori, Exponential speedup of quantum annealing by inhomogeneous driving of the transverse field, J. Phys. Soc. Jpn. 87, 023002 (2018).
- T. Albash, Role of nonstoquastic catalysts in quantum adiabatic optimization, Phys. Rev. A 99, 042334 (2019).
- C. Cao, J. Xue, N. Shannon, and R. Joynt, Speedup of the quantum adiabatic algorithm using delocalization catalysis, Phys. Rev. Res. 3, 013092 (2021).
- V. Mehta, F. Jin, H. De Raedt, and K. Michielsen, Quantum annealing with trigger Hamiltonians: Application to 2-satisfiability and nonstoquastic problems, Phys. Rev. A 104, 032421 (2021).
- E. Farhi, J. Goldstone, and S. Gutmann, A quantum approximate optimization algorithm, arXiv:1411.4028.
- L. Zhou, S.-T. Wang, S. Choi, H. Pichler, and M. D. Lukin, Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices, Phys. Rev. X 10, 021067 (2020).
- Z.-C. Yang, A. Rahmani, A. Shabani, H. Neven, and C. Chamon, Optimizing variational quantum algorithms using Pontryagin’s minimum principle, Phys. Rev. X 7, 021027 (2017).
- C. Lin, Y. Wang, G. Kolesov, and U. Kalabić, Application of Pontryagin’s minimum principle to Grover’s quantum search problem, Phys. Rev. A 100, 022327 (2019).
- L. T. Brady, C. L. Baldwin, A. Bapat, Y. Kharkov, and A. V. Gorshkov, Optimal protocols in quantum annealing and quantum approximate optimization algorithm problems, Phys. Rev. Lett. 126, 070505 (2021).
- J. Côté, F. Sauvage, M. Larocca, M. Jonsson, L. Cincio, and T. Albash, Diabatic quantum annealing for the frustrated ring model, Quantum Sci. Tech. 8, 045033 (2023).
- A. Grabarits, F. Balducci, B. C. Sanders, and A. del Campo, Non-adiabatic quantum optimization for crossing quantum phase transitions, Phys. Rev. A 111, 012215 (2025).
- S. Rice and M. Zhao, Optical Control of Molecular Dynamics, Baker Lecture Series (Wiley, 2000), ISBN: 978-0-471-35423-9.
- M. Demirplak and S. A. Rice, Adiabatic population transfer with control fields, J. Phys. Chem. A 107, 9937 (2003); Assisted adiabatic passage revisited, J. Phys. Chem. B 109, 6838 (2005); On the consistency, extremal, and global properties of counterdiabatic fields, J. Chem. Phys. 129, 154111 (2008).
- M. V. Berry, Transitionless quantum driving, J. Phys. A 42, 365303 (2009).
- T. Kato, On the adiabatic theorem of quantum mechanics, J. Phys. Soc. Jpn. 5, 435 (1950).
- A. del Campo, M. M. Rams, and W. H. Zurek, Assisted finite-rate adiabatic passage across a quantum critical point: Exact solution for the quantum Ising model, Phys. Rev. Lett. 109, 115703 (2012).
- K. Takahashi, Transitionless quantum driving for spin systems, Phys. Rev. E 87, 062117 (2013).
- B. Damski, Counterdiabatic driving of the quantum Ising model, J. Stat. Mech. Theory Exp. 2014, P12019 (2014).
- H. Saberi, T. Opatrný, K. Mølmer, and A. del Campo, Adiabatic tracking of quantum many-body dynamics, Phys. Rev. A 90, 060301(R) (2014).
- M. Kolodrubetz, D. Sels, P. Mehta, and A. Polkovnikov, Geometry and non-adiabatic response in quantum and classical systems, Phys. Rep. 697, 1 (2017).
- D. Sels and A. Polkovnikov, Minimizing irreversible losses in quantum systems by local counterdiabatic driving, Proc. Natl. Acad. Sci. U.S.A. 114, E3909 (2017).
- P. W. Claeys, M. Pandey, D. Sels, and A. Polkovnikov, Floquet-engineering counterdiabatic protocols in quantum many-body systems, Phys. Rev. Lett. 123, 090602 (2019).
- K. Takahashi and A. del Campo, Shortcuts to adiabaticity in Krylov space, Phys. Rev. X 14, 011032 (2024).
- B. Bhattacharjee, A Lanczos approach to the adiabatic gauge potential, arXiv:2302.07228.
- P. Chandarana, N. N. Hegade, K. Paul, F. Albarrán-Arriagada, E. Solano, A. del Campo, and X. Chen, Digitized-counterdiabatic quantum approximate optimization algorithm, Phys. Rev. Res. 4, 013141 (2022).
- N. N. Hegade, X. Chen, and E. Solano, Digitized counterdiabatic quantum optimization, Phys. Rev. Res. 4, L042030 (2022).
- J. Wurtz and P. J. Love, Counterdiabaticity and the quantum approximate optimization algorithm, Quantum 6, 635 (2022).
- N. N. Hegade and E. Solano, Digitized-counterdiabatic quantum factorization, arXiv:2301.11005.
- P. Chandarana, N. N. Hegade, I. Montalban, E. Solano, and X. Chen, Digitized counterdiabatic quantum algorithm for protein folding, Phys. Rev. Appl. 20, 014024 (2023).
- R. K. Malla, H. Sukeno, H. Yu, T.-C. Wei, A. Weichselbaum, and R. M. Konik, Feedback-based quantum algorithm inspired by counterdiabatic driving, Phys. Rev. Res. 6, 043068 (2024).
- P. Chandarana, K. Paul, K. R. Swain, X. Chen, and A. del Campo, Lyapunov controlled counterdiabatic quantum optimization, arXiv:2409.12525.
- T. Hatomura, Scaling of errors in digitized counterdiabatic driving, New J. Phys. 25, 103025 (2023).
- T. Hatomura, Shortcuts to adiabaticity: Theoretical framework, relations between different methods, and versatile approximations, J. Phys. B 57, 102001 (2024).
- M. S. Lucas Lamata, Adrian Parra-Rodriguez, and E. Solano, Digital-analog quantum simulations with superconducting circuits, Adv. Phys. X 3, 1457981 (2018).
- S. Kumar, N. N. Hegade, A. G. Cadavid, M. H. de Oliveira, E. Solano, and F. Albarrán-Arriagada, Digital-analog counterdiabatic quantum optimization with trapped ions, arXiv:2405.01447.
- S. Campbell, G. De Chiara, M. Paternostro, G. M. Palma, and R. Fazio, Shortcut to adiabaticity in the Lipkin-Meshkov-Glick model, Phys. Rev. Lett. 114, 177206 (2015).
- V. Mukherjee, S. Montangero, and R. Fazio, Local shortcut to adiabaticity for quantum many-body systems, Phys. Rev. A 93, 062108 (2016).
- E. Carolan, A. Kiely, and S. Campbell, Counterdiabatic control in the impulse regime, Phys. Rev. A 105, 012605 (2022).
- A. Hartmann, G. B. Mbeng, and W. Lechner, Polynomial scaling enhancement in the ground-state preparation of Ising spin models via counterdiabatic driving, Phys. Rev. A 105, 022614 (2022).
- I. Čepaitė, A. Polkovnikov, A. J. Daley, and C. W. Duncan, Counterdiabatic optimized local driving, PRX Quantum 4, 010312 (2023).
- C. Mc Keever and M. Lubasch, Towards adiabatic quantum computing using compressed quantum circuits, PRX Quantum 5, 020362 (2024).
- B. Damski, The simplest quantum model supporting the Kibble-Zurek mechanism of topological defect production: Landau-Zener transitions from a new perspective, Phys. Rev. Lett. 95, 035701 (2005).
- W. H. Zurek, U. Dorner, and P. Zoller, Dynamics of a quantum phase transition, Phys. Rev. Lett. 95, 105701 (2005).
- J. Dziarmaga, Dynamics of a quantum phase transition: Exact solution of the quantum Ising model, Phys. Rev. Lett. 95, 245701 (2005).
- A. Polkovnikov, Universal adiabatic dynamics in the vicinity of a quantum critical point, Phys. Rev. B 72, 161201(R) (2005).
- B. Damski and W. H. Zurek, Adiabatic-impulse approximation for avoided level crossings: From phase-transition dynamics to Landau-Zener evolutions and back again, Phys. Rev. A 73, 063405 (2006).
- A. del Campo and W. H. Zurek, Universality of phase transition dynamics: Topological defects from symmetry breaking, Int. J. Mod. Phys. A 29, 1430018 (2014).
- L.-Y. Qiu, H.-Y. Liang, Y.-B. Yang, H.-X. Yang, T. Tian, Y. Xu, and L.-M. Duan, Observation of generalized Kibble-Zurek mechanism across a first-order quantum phase transition in a spinor condensate, Sci. Adv. 6, eaba7292 (2020).
- F. Suzuki and W. H. Zurek, Topological defect formation in a phase transition with tunable order, Phys. Rev. Lett. 132, 241601 (2024).
- A. G. Cadavid, A. Dalal, A. Simen, E. Solano, and N. N. Hegade, Bias-field digitized counterdiabatic quantum optimization, Phys. Rev. Res. 7, L022010 (2025).
- G. Passarelli, V. Cataudella, R. Fazio, and P. Lucignano, Counterdiabatic driving in the quantum annealing of the -spin model: A variational approach, Phys. Rev. Res. 2, 013283 (2020).
- L. Prielinger, A. Hartmann, Y. Yamashiro, K. Nishimura, W. Lechner, and H. Nishimori, Two-parameter counter-diabatic driving in quantum annealing, Phys. Rev. Res. 3, 013227 (2021).
- M. Gong, X. Wen, G. Sun, D.-W. Zhang, D. Lan, Y. Zhou, Y. Fan, Y. Liu, X. Tan, H. Yu, Y. Yu, S.-L. Zhu, S. Han, and P. Wu, Simulating the Kibble-Zurek mechanism of the Ising model with a superconducting qubit system, Sci. Rep. 6, 22667 (2016).
- J.-M. Cui, Y.-F. Huang, Z. Wang, D.-Y. Cao, J. Wang, W.-M. Lv, L. Luo, A. del Campo, Y.-J. Han, C.-F. Li, and G.-C. Guo, Experimental trapped-ion quantum simulation of the Kibble-Zurek dynamics in momentum space, Sci. Rep. 6, 33381 (2016).
- J.-M. Cui, F. J. Gómez-Ruiz, Y.-F. Huang, C.-F. Li, G.-C. Guo, and A. del Campo, Experimentally testing quantum critical dynamics beyond the Kibble–Zurek mechanism, Commun. Phys. 3, 44 (2020).
- A. Keesling, A. Omran, H. Levine, H. Bernien, H. Pichler, S. Choi, R. Samajdar, S. Schwartz, P. Silvi, S. Sachdev, P. Zoller, M. Endres, M. Greiner, V. Vuletic, and M. D. Lukin, Quantum Kibble–Zurek mechanism and critical dynamics on a programmable Rydberg simulator, Nature 568, 207 (2019).
- B. Gardas, J. Dziarmaga, W. H. Zurek, and M. Zwolak, Defects in quantum computers, Sci. Rep. 8, 4539 (2018).
- P. Weinberg, M. Tylutki, J. M. Rönkkö, J. Westerholm, J. A. Åström, P. Manninen, P. Törmä, and A. W. Sandvik, Scaling and diabatic effects in quantum annealing with a D-wave device, Phys. Rev. Lett. 124, 090502 (2020).
- Y. Bando, Y. Susa, H. Oshiyama, N. Shibata, M. Ohzeki, F. J. Gómez-Ruiz, D. A. Lidar, S. Suzuki, A. del Campo, and H. Nishimori, Probing the universality of topological defect formation in a quantum annealer: Kibble-Zurek mechanism and beyond, Phys. Rev. Res. 2, 033369 (2020).
- A. D. King et al., Coherent quantum annealing in a programmable 2000-qubit Ising chain, Nat. Phys. 18, 1324 (2022).
- A. D. King et al., Beyond-classical computation in quantum simulation, Science 388, 199 (2025).
- D. Roberts, L. Cincio, A. Saxena, A. Petukhov, and S. Knysh, Noise amplification at spin-glass bottlenecks of quantum annealing: A solvable model, Phys. Rev. A 101, 042317 (2020).
- M. V. Berry, Quantal phase factors accompanying adiabatic changes, Proc. R. Soc. London A 392, 45 (1984).
- J. Yao, L. Lin, and M. Bukov, Reinforcement learning for many-body ground-state preparation inspired by counterdiabatic driving, Phys. Rev. X 11, 031070 (2021).
- M. Ohkuwa, H. Nishimori, and D. A. Lidar, Reverse annealing for the fully connected -spin model, Phys. Rev. A 98, 022314 (2018).
- A. D. King et al., Observation of topological phenomena in a programmable lattice of 1800 qubits, Nature 560, 456 (2018).
- Y. Yamashiro, M. Ohkuwa, H. Nishimori, and D. A. Lidar, Dynamics of reverse annealing for the fully connected -spin model, Phys. Rev. A 100, 052321 (2019).
- S. Boixo, T. F. Rønnow, S. V. Isakov, Z. Wang, D. Wecker, D. A. Lidar, J. M. Martinis, and M. Troyer, Evidence for quantum annealing with more than one hundred qubits, Nat. Phys. 10, 218 (2014).
- A. Carlini, A. Hosoya, T. Koike, and Y. Okudaira, Time-optimal quantum evolution, Phys. Rev. Lett. 96, 060503 (2006).
- C. M. Bender and D. C. Brody, in Time in Quantum Mechanics, edited by G. Muga, A. Ruschhaupt, and A. del Campo (Springer, Berlin, 2009), Vol. 2, p. 341.
- K. Takahashi, How fast and robust is the quantum adiabatic passage? J. Phys. A 46, 315304 (2013).
- S. V. Romero, A.-M. Visuri, A. G. Cadavid, A. Simen, E. Solano, and N. N. Hegade, Bias-field digitized counterdiabatic quantum algorithm for higher-order binary optimization, Commun. Phys. 8, 348 (2025).
- S. V. Romero, A. G. Cadavid, P. Nikačević, E. Solano, N. N. Hegade, M. A. Lopez-Ruiz, C. Girotto, M. Yamada, P. K. Barkoutsos, A. Kaushik, and M. Roetteler, Protein folding with an all-to-all trapped-ion quantum computer, arXiv:2506.07866.
- O. Abah, R. Puebla, A. Kiely, G. D. Chiara, M. Paternostro, and S. Campbell, Energetic cost of quantum control protocols, New J. Phys. 21, 103048 (2019).
- E. Torrontegui, I. Lizuain, S. González-Resines, A. Tobalina, A. Ruschhaupt, R. Kosloff, and J. G. Muga, Energy consumption for shortcuts to adiabaticity, Phys. Rev. A 96, 022133 (2017).
- S. Campbell and S. Deffner, Trade-off between speed and cost in shortcuts to adiabaticity, Phys. Rev. Lett. 118, 100601 (2017).
- K. Funo, J.-N. Zhang, C. Chatou, K. Kim, M. Ueda, and A. del Campo, Universal work fluctuations during shortcuts to adiabaticity by counterdiabatic driving, Phys. Rev. Lett. 118, 100602 (2017).
- E. Farhi, D. Gosset, I. Hen, A. W. Sandvik, P. Shor, A. P. Young, and F. Zamponi, Performance of the quantum adiabatic algorithm on random instances of two optimization problems on regular hypergraphs, Phys. Rev. A 86, 052334 (2012).
- T. Albash and D. A. Lidar, Adiabatic quantum computation, Rev. Mod. Phys. 90, 015002 (2018).
- J. Tindall, A. Mello, M. Fishman, M. Stoudenmire, and D. Sels, Dynamics of disordered quantum systems with two- and three-dimensional tensor networks, arXiv:2503.05693.
- L. Mauron and G. Carleo, Challenging the quantum advantage frontier with large-scale classical simulations of annealing dynamics, arXiv:2503.08247.
- S. Morawetz and A. Polkovnikov, Efficient paths for local counterdiabatic driving, Phys. Rev. B 110, 024304 (2024).
- A.-M. Visuri, A. G. Cadavid, B. A. Bhargava, S. V. Romero, A. Grabarits, P. Chandarana, E. Solano, A. del Campo, and N. N. Hegade, Digitized counterdiabatic quantum critical dynamics, arXiv:2502.15100.
- M. Bellitti, F. Ricci-Tersenghi, and A. Scardicchio, Entropic barriers as a reason for hardness in both classical and quantum algorithms, Phys. Rev. Res. 3, 043015 (2021).
- J. R. McClean, S. Boixo, V. N. Smelyanskiy, R. Babbush, and H. Neven, Barren plateaus in quantum neural network training landscapes, Nat. Commun. 9, 4812 (2018).
- Alexandre G. R. Day, M. Bukov, P. Weinberg, P. Mehta, and D. Sels, Glassy phase of optimal quantum control, Phys. Rev. Lett. 122, 020601 (2019).
- M. Larocca, S. Thanasilp, S. Wang, K. Sharma, J. Biamonte, P. J. Coles, L. Cincio, J. R. McClean, Z. Holmes, and M. Cerezo, Barren plateaus in variational quantum computing, Nat. Rev. Phys. 7, 174 (2025).
- N. Beato, P. Patil, and M. Bukov, Toward a theory of phase transitions in quantum control landscapes, Phys. Rev. X 15, 041014 (2025).
- M. M. Rams, J. Dziarmaga, and W. H. Zurek, Symmetry breaking bias and the dynamics of a quantum phase transition, Phys. Rev. Lett. 123, 130603 (2019).
- J. K. Asbóth, L. Oroszlány, and A. Pályi, A Short Course on Topological Insulators: Band Structure and Edge States in One and Two Dimensions (Springer International, Cham, 2016).
- N. Seiberg and S.-H. Shao, Majorana chain and Ising model—(Non-invertible) translations, anomalies, and emanant symmetries, SciPost Phys. 16, 064 (2024).
- E. Lieb, T. Schultz, and D. Mattis, Two soluble models of an antiferromagnetic chain, Ann. Phys. 16, 407 (1961).
- O. A. Prośniak, On the size of boundary effects in the Ising chain, Phys. Scr. 94, 085201 (2019).
- G. B. Mbeng, A. Russomanno, and G. E. Santoro, The quantum Ising chain for beginners, SciPost Phys. Lect. Notes, 82 (2024).
- J. Surace and L. Tagliacozzo, Fermionic Gaussian states: An introduction to numerical approaches, SciPost Phys. Lect. Notes, 54 (2022).
