Pub Date : 2026-01-07DOI: 10.1088/2058-9565/ae3028
Qiaofeng Liu, Ian Low and Zhewei Yin
Magic is a quantum resource essential for universal quantum computation and represents the deviation of quantum states from those that can be simulated efficiently using classical algorithms. Using the stabilizer Rényi entropy (SRE), we investigate two-qubit states with maximal magic, which are most distinct from classical simulability, and provide strong numerical evidence that the maximal second order SRE is , establishing a tighter bound than the prior . We identify 480 states saturating the new bound, which turn out to be the fiducial states for the mutually unbiased bases (MUBs) generated by the orbits of the Weyl–Heisenberg (WH) group, and conjecture that WH-MUBs are the maximal magic states for n-qubit, when n ≠ 1 and 3. We also reveal a striking interplay between magic and entanglement: the entanglement of maximal magic states is restricted to two possible values, and , as quantified by the concurrence; none is maximally entangled.
{"title":"Maximal magic for two-qubit states","authors":"Qiaofeng Liu, Ian Low and Zhewei Yin","doi":"10.1088/2058-9565/ae3028","DOIUrl":"https://doi.org/10.1088/2058-9565/ae3028","url":null,"abstract":"Magic is a quantum resource essential for universal quantum computation and represents the deviation of quantum states from those that can be simulated efficiently using classical algorithms. Using the stabilizer Rényi entropy (SRE), we investigate two-qubit states with maximal magic, which are most distinct from classical simulability, and provide strong numerical evidence that the maximal second order SRE is , establishing a tighter bound than the prior . We identify 480 states saturating the new bound, which turn out to be the fiducial states for the mutually unbiased bases (MUBs) generated by the orbits of the Weyl–Heisenberg (WH) group, and conjecture that WH-MUBs are the maximal magic states for n-qubit, when n ≠ 1 and 3. We also reveal a striking interplay between magic and entanglement: the entanglement of maximal magic states is restricted to two possible values, and , as quantified by the concurrence; none is maximally entangled.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"40 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145908302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-06DOI: 10.1088/2058-9565/ae2efa
Dmitrii Khitrin, Kenneth R Brown and Abhinav Anand
Unitary errors, such as those arising from fault-tolerant (FT) compilation of quantum algorithms, systematically bias observable estimates. Correcting this bias typically requires additional resources, such as an increased number of non-Clifford gates. In this work, we present an alternative method for correcting bias in the expectation values of observables. The method leverages a decomposition of the ideal quantum channel into a probabilistic mixture of noisy quantum channels. Using this decomposition, we construct unbiased estimators as weighted sums of expectation values obtained from the noisy channels. We provide a detailed analysis of the method, identify the conditions under which it is effective, and validate its performance through numerical simulations. In particular, we demonstrate unbiased observable estimation in the presence of unitary errors by simulating the time dynamics of the Ising Hamiltonian. Our strategy offers a resource-efficient way to reduce the impact of unitary errors, improving methods for estimating observables in noisy near-term quantum devices and FT implementation of quantum algorithms.
{"title":"Unbiased observable estimation with approximate channels in fault-tolerant quantum computation","authors":"Dmitrii Khitrin, Kenneth R Brown and Abhinav Anand","doi":"10.1088/2058-9565/ae2efa","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2efa","url":null,"abstract":"Unitary errors, such as those arising from fault-tolerant (FT) compilation of quantum algorithms, systematically bias observable estimates. Correcting this bias typically requires additional resources, such as an increased number of non-Clifford gates. In this work, we present an alternative method for correcting bias in the expectation values of observables. The method leverages a decomposition of the ideal quantum channel into a probabilistic mixture of noisy quantum channels. Using this decomposition, we construct unbiased estimators as weighted sums of expectation values obtained from the noisy channels. We provide a detailed analysis of the method, identify the conditions under which it is effective, and validate its performance through numerical simulations. In particular, we demonstrate unbiased observable estimation in the presence of unitary errors by simulating the time dynamics of the Ising Hamiltonian. Our strategy offers a resource-efficient way to reduce the impact of unitary errors, improving methods for estimating observables in noisy near-term quantum devices and FT implementation of quantum algorithms.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-31DOI: 10.1088/2058-9565/ae2d8d
Christopher Mastandrea, Costin Iancu, Hao Guo, Chih-Chun Chien
A spin-1 system can exhibit an intermediate-temperature topological regime with a quantized Uhlmann phase sandwiched by topologically trivial low- and high-temperature regimes. We present a quantum circuit consisting of system and ancilla qubits plus a probe qubit which prepares an initial state corresponding to the purified state of a spin-1 system at finite temperature, evolves the system according to the Uhlmann process, and measures the Uhlmann phase via expectation values of the probe qubit. Although classical simulations suggest the quantized Uhlmann phase is observable on International Business Machines (IBM’s) noisy intermediate-scale quantum (NISQ) computers, an implementation of the circuit without any optimization exceeds the gate count for the error budget and results in unresolved signals. Through a series of optimization with Qiskit and BQSKit, the gate count can be substantially reduced, making the jumps of the Uhlmann phase more visible. A recent hardware upgrade of IBM quantum computers further improves the signals and leads to a clearer demonstration of interesting finite-temperature topological phenomena on NISQ hardware.
{"title":"Intermediate-temperature topological Uhlmann phase on IBM quantum computers","authors":"Christopher Mastandrea, Costin Iancu, Hao Guo, Chih-Chun Chien","doi":"10.1088/2058-9565/ae2d8d","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2d8d","url":null,"abstract":"A spin-1 system can exhibit an intermediate-temperature topological regime with a quantized Uhlmann phase sandwiched by topologically trivial low- and high-temperature regimes. We present a quantum circuit consisting of system and ancilla qubits plus a probe qubit which prepares an initial state corresponding to the purified state of a spin-1 system at finite temperature, evolves the system according to the Uhlmann process, and measures the Uhlmann phase via expectation values of the probe qubit. Although classical simulations suggest the quantized Uhlmann phase is observable on International Business Machines (IBM’s) noisy intermediate-scale quantum (NISQ) computers, an implementation of the circuit without any optimization exceeds the gate count for the error budget and results in unresolved signals. Through a series of optimization with Qiskit and BQSKit, the gate count can be substantially reduced, making the jumps of the Uhlmann phase more visible. A recent hardware upgrade of IBM quantum computers further improves the signals and leads to a clearer demonstration of interesting finite-temperature topological phenomena on NISQ hardware.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"24 1","pages":"015033"},"PeriodicalIF":6.7,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-31DOI: 10.1088/2058-9565/ae302a
Xuan Zuo, Zi-Xu Lu, Jie Li
The strong coupling between light and matter gives rise to polaritons. Further coupling polaritons to phonons leads to the formation of hybrid polaromechanical systems. Recent experiments have achieved the strong coupling between polaritons and phonons in two configurations, namely, the magnon–photon–phonon and exciton–photon–phonon systems, which enables the control of mechanical motion via manipulating polaritons. Here, we present a polaromechanical cooling theory and explicitly show how two polaritons can be used to simultaneously cool two mechanical modes. The unique advantage of our protocol lies in the fact that the continuous tunability of the polariton frequencies over a wide range allows for the cooling of any two mechanical modes with their frequency difference falling within this range. We further discuss how to extend the theory to cool multiple mechanical modes. The protocol is designed for cooling mechanical motion in various emerging polaromechanical platforms, such as magnon-, exciton-, and plasmon-polaromechanical systems, which is the first step towards quantum states generation in these hybrid systems.
{"title":"Cooling mechanical motion with polaritons","authors":"Xuan Zuo, Zi-Xu Lu, Jie Li","doi":"10.1088/2058-9565/ae302a","DOIUrl":"https://doi.org/10.1088/2058-9565/ae302a","url":null,"abstract":"The strong coupling between light and matter gives rise to polaritons. Further coupling polaritons to phonons leads to the formation of hybrid polaromechanical systems. Recent experiments have achieved the strong coupling between polaritons and phonons in two configurations, namely, the magnon–photon–phonon and exciton–photon–phonon systems, which enables the control of mechanical motion via manipulating polaritons. Here, we present a polaromechanical cooling theory and explicitly show how two polaritons can be used to simultaneously cool two mechanical modes. The unique advantage of our protocol lies in the fact that the continuous tunability of the polariton frequencies over a wide range allows for the cooling of any two mechanical modes with their frequency difference falling within this range. We further discuss how to extend the theory to cool multiple mechanical modes. The protocol is designed for cooling mechanical motion in various emerging polaromechanical platforms, such as magnon-, exciton-, and plasmon-polaromechanical systems, which is the first step towards quantum states generation in these hybrid systems.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"25 1","pages":"015032"},"PeriodicalIF":6.7,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-29DOI: 10.1088/2058-9565/ae2d8e
Asghar Ullah, Özgür E Müstecaplıoğlu, Matteo G A Paris
We investigate the optimization of graph topologies for quantum sensing networks designed to estimate weak magnetic fields. The sensors are modeled as spin systems governed by a transverse-field Ising Hamiltonian in thermal equilibrium at low temperatures. Using a genetic algorithm (GA), we evolve network topologies to maximize a perturbative spectral sensitivity measure, which serves as the fitness function for the GA. For the best-performing graphs, we compute the corresponding quantum Fisher information (QFI) to assess the ultimate bounds on estimation precision. To enable efficient scaling, we use the GA-generated data to train a deep neural network, allowing extrapolation to larger graph sizes where direct computation becomes prohibitive. Our results show that while both the fitness function and QFI initially increase with system size, the QFI exhibits a clear non-monotonic behavior—saturating and eventually declining beyond a critical graph size. This reflects the loss of superlinear scaling of the QFI, as the narrowing of the energy gap signals a crossover to classical scaling of the QFI with system size. The effect is reminiscent of the microeconomic law of diminishing returns: beyond an optimal graph size, further increases yield reduced sensing performance. This saturation and decline in precision are particularly pronounced under Kac scaling, where both the QFI and spin squeezing plateau or degrade with increasing system size. We also attribute observed even–odd oscillations in the spectral sensitivity measure and QFI to quantum interference effects in spin phase space, as confirmed by our phase-space analysis. These findings highlight the critical role of optimizing interaction topology—rather than simply increasing network size—and demonstrate the potential of hybrid evolutionary and learning-based approaches for designing high-performance quantum sensors.
{"title":"Optimizing quantum sensing networks via genetic algorithms and deep learning","authors":"Asghar Ullah, Özgür E Müstecaplıoğlu, Matteo G A Paris","doi":"10.1088/2058-9565/ae2d8e","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2d8e","url":null,"abstract":"We investigate the optimization of graph topologies for quantum sensing networks designed to estimate weak magnetic fields. The sensors are modeled as spin systems governed by a transverse-field Ising Hamiltonian in thermal equilibrium at low temperatures. Using a genetic algorithm (GA), we evolve network topologies to maximize a perturbative spectral sensitivity measure, which serves as the fitness function for the GA. For the best-performing graphs, we compute the corresponding quantum Fisher information (QFI) to assess the ultimate bounds on estimation precision. To enable efficient scaling, we use the GA-generated data to train a deep neural network, allowing extrapolation to larger graph sizes where direct computation becomes prohibitive. Our results show that while both the fitness function and QFI initially increase with system size, the QFI exhibits a clear non-monotonic behavior—saturating and eventually declining beyond a critical graph size. This reflects the loss of superlinear scaling of the QFI, as the narrowing of the energy gap signals a crossover to classical scaling of the QFI with system size. The effect is reminiscent of the microeconomic law of diminishing returns: beyond an optimal graph size, further increases yield reduced sensing performance. This saturation and decline in precision are particularly pronounced under Kac scaling, where both the QFI and spin squeezing plateau or degrade with increasing system size. We also attribute observed even–odd oscillations in the spectral sensitivity measure and QFI to quantum interference effects in spin phase space, as confirmed by our phase-space analysis. These findings highlight the critical role of optimizing interaction topology—rather than simply increasing network size—and demonstrate the potential of hybrid evolutionary and learning-based approaches for designing high-performance quantum sensors.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"89 1","pages":"015031"},"PeriodicalIF":6.7,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145894254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-23DOI: 10.1088/2058-9565/ae2c16
Leander Grech, Matthias G Krauss, Mirko Consiglio, Tony J G Apollaro, Christiane P Koch, Simon Hirlaender and Gianluca Valentino
Noisy intermediate-scale quantum computers hold the promise of tackling complex and otherwise intractable computational challenges through the massive parallelism offered by qubits. Central to realizing the potential of quantum computing are perfect entangling (PE) two-qubit gates, which serve as a critical building block for universal quantum computation. In the context of quantum optimal control, shaping electromagnetic pulses to drive quantum gates is crucial for pushing gate performance toward theoretical limits. In this work, we leverage reinforcement learning (RL) techniques to discover near-optimal pulse shapes that yield PE gates. A collection of RL agents is trained within robust simulation environments, enabling the identification of effective control strategies even under noisy conditions. Selected agents are then validated on higher-fidelity simulations, illustrating how RL-based methods can reduce calibration overhead when compared to quantum optimal control techniques. Furthermore, the RL approach is hardware agnostic with the potential for broad applicability across various quantum computing platforms.
{"title":"Achieving fast and robust perfect entangling gates via reinforcement learning","authors":"Leander Grech, Matthias G Krauss, Mirko Consiglio, Tony J G Apollaro, Christiane P Koch, Simon Hirlaender and Gianluca Valentino","doi":"10.1088/2058-9565/ae2c16","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2c16","url":null,"abstract":"Noisy intermediate-scale quantum computers hold the promise of tackling complex and otherwise intractable computational challenges through the massive parallelism offered by qubits. Central to realizing the potential of quantum computing are perfect entangling (PE) two-qubit gates, which serve as a critical building block for universal quantum computation. In the context of quantum optimal control, shaping electromagnetic pulses to drive quantum gates is crucial for pushing gate performance toward theoretical limits. In this work, we leverage reinforcement learning (RL) techniques to discover near-optimal pulse shapes that yield PE gates. A collection of RL agents is trained within robust simulation environments, enabling the identification of effective control strategies even under noisy conditions. Selected agents are then validated on higher-fidelity simulations, illustrating how RL-based methods can reduce calibration overhead when compared to quantum optimal control techniques. Furthermore, the RL approach is hardware agnostic with the potential for broad applicability across various quantum computing platforms.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"22 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1088/2058-9565/ae2b31
Alon Levi, Ziv Ossi, Eliahu Cohen and Amit Te’eni
A hybrid quantum–classical algorithm is a computational scheme in which quantum circuits are used to extract information that is then processed by a classical routine to guide subsequent quantum operations. These algorithms are especially valuable in the noisy intermediate-scale quantum era, where quantum resources are constrained and classical optimization plays a central role. Here, we improve the performance of a hybrid algorithm through principled, information-theoretic optimization. We focus on Quantum Likelihood Estimation (QLE)–-a hybrid algorithm designed to identify the Hamiltonian governing a quantum system by iteratively updating a weight distribution based on measurement outcomes and Bayesian inference. While QLE already achieves convergence using quantum measurements and Bayesian inference, its efficiency can vary greatly depending on the choice of parameters at each step. We propose an optimization strategy that dynamically selects the initial state, measurement basis, and evolution time in each iteration to maximize the mutual information between the measurement outcome and the true Hamiltonian. This approach builds upon the information-theoretic framework recently developed in Te’eni et al (2024 arXiv:2409.15549), and leverages mutual information as a guiding cost function for parameter selection. Our implementation employs a simulated annealing routine to minimize the conditional von Neumann entropy, thereby maximizing information gain in each iteration. The results demonstrate that our optimized version significantly reduces the number of iterations required for convergence, thus proposing a practical method for accelerating Hamiltonian learning in quantum systems. Finally, we propose a general scheme that extends our approach to solve a broader family of quantum learning problems.
{"title":"Optimal quantum likelihood estimation","authors":"Alon Levi, Ziv Ossi, Eliahu Cohen and Amit Te’eni","doi":"10.1088/2058-9565/ae2b31","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2b31","url":null,"abstract":"A hybrid quantum–classical algorithm is a computational scheme in which quantum circuits are used to extract information that is then processed by a classical routine to guide subsequent quantum operations. These algorithms are especially valuable in the noisy intermediate-scale quantum era, where quantum resources are constrained and classical optimization plays a central role. Here, we improve the performance of a hybrid algorithm through principled, information-theoretic optimization. We focus on Quantum Likelihood Estimation (QLE)–-a hybrid algorithm designed to identify the Hamiltonian governing a quantum system by iteratively updating a weight distribution based on measurement outcomes and Bayesian inference. While QLE already achieves convergence using quantum measurements and Bayesian inference, its efficiency can vary greatly depending on the choice of parameters at each step. We propose an optimization strategy that dynamically selects the initial state, measurement basis, and evolution time in each iteration to maximize the mutual information between the measurement outcome and the true Hamiltonian. This approach builds upon the information-theoretic framework recently developed in Te’eni et al (2024 arXiv:2409.15549), and leverages mutual information as a guiding cost function for parameter selection. Our implementation employs a simulated annealing routine to minimize the conditional von Neumann entropy, thereby maximizing information gain in each iteration. The results demonstrate that our optimized version significantly reduces the number of iterations required for convergence, thus proposing a practical method for accelerating Hamiltonian learning in quantum systems. Finally, we propose a general scheme that extends our approach to solve a broader family of quantum learning problems.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"56 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145777639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-17DOI: 10.1088/2058-9565/ae2887
Maria-Andreea Filip and Nathan Fitzpatrick
We consider a quantum algorithm for ground-state preparation based on a Chebyshev series approximation to the wall function. In a classical setting, this approach is appealing as it guarantees rapid convergence. We analyse the asymptotic scaling and success probabilities of different quantum implementations and provide numerical benchmarks, comparing the performance of the wall-Chebyshev projectors with current state-of-the-art approaches. We find that this approach requires fewer serial applications of the Hamiltonian oracle to achieve a given ground state fidelity, but is severely limited by exponentially decaying success probability. However, we find that some implementations maintain non-trivial success probability in regimes where wall-Chebyshev projection leads to a fidelity improvement over other approaches. As the wall-Chebyshev projector is highly robust to loose known upper bounds on the true ground state energy, it offers a potential resource trade-off, particularly in the early fault-tolerant regime of quantum computation.
{"title":"Beyond asymptotic reasoning: the practicalities of a quantum ground state projector based on the wall-Chebyshev expansion","authors":"Maria-Andreea Filip and Nathan Fitzpatrick","doi":"10.1088/2058-9565/ae2887","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2887","url":null,"abstract":"We consider a quantum algorithm for ground-state preparation based on a Chebyshev series approximation to the wall function. In a classical setting, this approach is appealing as it guarantees rapid convergence. We analyse the asymptotic scaling and success probabilities of different quantum implementations and provide numerical benchmarks, comparing the performance of the wall-Chebyshev projectors with current state-of-the-art approaches. We find that this approach requires fewer serial applications of the Hamiltonian oracle to achieve a given ground state fidelity, but is severely limited by exponentially decaying success probability. However, we find that some implementations maintain non-trivial success probability in regimes where wall-Chebyshev projection leads to a fidelity improvement over other approaches. As the wall-Chebyshev projector is highly robust to loose known upper bounds on the true ground state energy, it offers a potential resource trade-off, particularly in the early fault-tolerant regime of quantum computation.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"12 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-17DOI: 10.1088/2058-9565/ae2885
Danilo Triggiani and Cosmo Lupo
The Rayleigh diffraction limit imposes a fundamental restriction on the resolution of direct imaging systems, hindering the identification of incoherent optical sources, such as celestial bodies in astronomy and fluorophores in bioimaging. Recent advances in quantum sensing have shown that this limit can be circumvented through spatial demultiplexing (SPADE) and photon detection, i.e. a semi-classical detection strategy. However, the general optimality for arbitrary intensity distributions and bright sources remains unproven. In this work, we develop a general model for incoherent light with arbitrary intensity undergoing diffraction. We employ this framework to compute the quantum Chernoff exponent for generic incoherent-source discrimination problems, focusing on the sub-diffraction regime. We show that, surprisingly, SPADE measurements saturate the quantum Chernoff bound only when certain compatibility conditions are met. These findings suggest that collective measurements may actually be needed to achieve the ultimate quantum Chernoff bound for the discrimination of specific incoherent sources. For the fully general case, our analysis can still be used to find the best SPADE configurations, generally achieved through a rotation of the SPADE interferometer that depends on the discrimination task. We also simulated the efficiency of a simplified Bayesian test that we developed for this identification task and show that the saturation of the Chernoff bound is already achieved for a finite number of repetitions . Our results advance the theory of quantum-limited optical discrimination, with possible applications in diagnostics, automated image interpretation, and galaxy identification.
{"title":"Achieving quantum-limited sub-Rayleigh identification of incoherent optical sources with arbitrary intensities","authors":"Danilo Triggiani and Cosmo Lupo","doi":"10.1088/2058-9565/ae2885","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2885","url":null,"abstract":"The Rayleigh diffraction limit imposes a fundamental restriction on the resolution of direct imaging systems, hindering the identification of incoherent optical sources, such as celestial bodies in astronomy and fluorophores in bioimaging. Recent advances in quantum sensing have shown that this limit can be circumvented through spatial demultiplexing (SPADE) and photon detection, i.e. a semi-classical detection strategy. However, the general optimality for arbitrary intensity distributions and bright sources remains unproven. In this work, we develop a general model for incoherent light with arbitrary intensity undergoing diffraction. We employ this framework to compute the quantum Chernoff exponent for generic incoherent-source discrimination problems, focusing on the sub-diffraction regime. We show that, surprisingly, SPADE measurements saturate the quantum Chernoff bound only when certain compatibility conditions are met. These findings suggest that collective measurements may actually be needed to achieve the ultimate quantum Chernoff bound for the discrimination of specific incoherent sources. For the fully general case, our analysis can still be used to find the best SPADE configurations, generally achieved through a rotation of the SPADE interferometer that depends on the discrimination task. We also simulated the efficiency of a simplified Bayesian test that we developed for this identification task and show that the saturation of the Chernoff bound is already achieved for a finite number of repetitions . Our results advance the theory of quantum-limited optical discrimination, with possible applications in diagnostics, automated image interpretation, and galaxy identification.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"7 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145771414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-16DOI: 10.1088/2058-9565/ae2884
Nicolas Dirnegger, Moein Malekakhlagh, Vikesh Siddhu, Ashutosh Rao, Chi Xiong, Muir Kumph, Jason Orcutt and Abram Falk
A promising quantum computing architecture comprises modules of superconducting quantum processors linked via optical channels using quantum transducers. As quantum transducer hardware improves, a need has arisen to understand the quantitative relationship between transducer-device characteristics and the strength of the resulting remote entanglement. Using Monte Carlo simulations that incorporate 2-to-1 and 3-to-1 entanglement distillation methods, our model maps transducer device performance up to system-level channel performance, thereby allowing the performance of remote entanglement approaches to be compared and optimized. We find the extreme photon loss (EPL) distillation protocol to be particularly high performing. Moreover, even without distillation, present-day transducers with added noise of photons are at the threshold of enabling remote Bell pairs with fidelities exceeding 50%. If the next generation of transducers can improve by 3 orders of magnitude in added noise, efficiency, and repetition rates, then they would allow for remote two-qubit gates achieving 99.7% fidelities at MHz rates. These results set practical targets for transducers to be ready for deployment into modular quantum computing systems.
{"title":"Distilled remote entanglement between superconducting qubits across optical channels","authors":"Nicolas Dirnegger, Moein Malekakhlagh, Vikesh Siddhu, Ashutosh Rao, Chi Xiong, Muir Kumph, Jason Orcutt and Abram Falk","doi":"10.1088/2058-9565/ae2884","DOIUrl":"https://doi.org/10.1088/2058-9565/ae2884","url":null,"abstract":"A promising quantum computing architecture comprises modules of superconducting quantum processors linked via optical channels using quantum transducers. As quantum transducer hardware improves, a need has arisen to understand the quantitative relationship between transducer-device characteristics and the strength of the resulting remote entanglement. Using Monte Carlo simulations that incorporate 2-to-1 and 3-to-1 entanglement distillation methods, our model maps transducer device performance up to system-level channel performance, thereby allowing the performance of remote entanglement approaches to be compared and optimized. We find the extreme photon loss (EPL) distillation protocol to be particularly high performing. Moreover, even without distillation, present-day transducers with added noise of photons are at the threshold of enabling remote Bell pairs with fidelities exceeding 50%. If the next generation of transducers can improve by 3 orders of magnitude in added noise, efficiency, and repetition rates, then they would allow for remote two-qubit gates achieving 99.7% fidelities at MHz rates. These results set practical targets for transducers to be ready for deployment into modular quantum computing systems.","PeriodicalId":20821,"journal":{"name":"Quantum Science and Technology","volume":"3 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145760238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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