Quantum Physics · Cross-listed from hep-th
Strong-to-Weak Spontaneous Symmetry Breaking from Wormholes in Holography
Taishi Kawamoto, Kenya Tasuki and Masahito Yamazaki
We study strong-to-weak spontaneous
symmetry breaking (SWSSB) at finite temperature and its implications in holography. SWSSB is a novel critical phenomenon that arises only in mixed states. We demonstrate SWSSB with the BTZ black hole and show that, in the bulk, it is realized through wormhole geometries connecting the two copies in the thermofield-double construction. We point out that SWSSB can be recast as an emergence of global
symmetries under ensemble averaging. We further examine the interplay between SWSSB and the swampland program, and propose a new swampland
conjecture for
quantum-
gravity theories involving ensemble averages.
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Quantum Physics · Cross-listed from hep-ph
Decoherence and More Coherence in the Radiative Decay of the $Z$ Boson
Kun Cheng, Tao Han, Harman Singh et al. (+1 more)
Final state radiation in
collider processes can be interpreted as interactions with unobserved degrees of freedom and is often discussed within the context of decoherence of an entangled state. We consider the radiative decay of the $Z$
boson as a representative example and perform a detailed analytical study of the $\tau^-\tau^+\gamma$
spin state, as determined by the
chiral interactions of the Standard Model, over the complete three-body phase space. We explore various
quantum information observables to quantify how the $\tau^-\tau^+$
spin state changes with the
photon radiation. We find some striking features, for example that the emitted
photon could either lead to decoherence or monotonic enhancement of
entanglement for the
fermion pair.
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All authors Kun Cheng, Tao Han, Harman Singh, Youle Su
Quantum Physics
Remote Entanglement of Solid-State Spin Qubits Integrated in Broadband Waveguides
Christopher Waas, Timo Dolné, Hans K.C. Beukers et al. (+4 more)
Solid-state
spin-
photon interfaces promise to scale
quantum networks through on-chip photonic integration and multiplexed
entanglement generation. To date, remote
entanglement between integrated emitters has been realized only in cavity-enhanced systems, where fabrication yield and spectral matching remain major obstacles. Here we demonstrate heralded remote
entanglement between diamond tin-vacancy
spin qubits embedded in separate on-chip waveguides. Combining intrinsically efficient
photon emission with a broadband waveguide architecture provides high device yield and obviates the need for spectral matching to cavity modes. We realize coherent optical and
spin control and achieve high-visibility two-
photon interference. By combining
photon-mediated
entanglement generation with real-time feedforward, we produce a consistent entangled state independent of the heralding pattern. These results establish waveguide-integrated tin-vacancy centers as a compelling platform for scalable
quantum network nodes.
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All authors Christopher Waas, Timo Dolné, Hans K.C. Beukers, Alexander M. Stramma, Nina Codreanu, Noé Mathieu, Ronald Hanson
Quantum Physics
Quantum-classical neurons upgraded with optical spin qubits for advanced computing and networking architectures
Osama M. Nayfeh
Hardware
neurons incorporating built-in
memory components are critical technologies for implementing large scale neural networks that exhibit adaptive-itinerant behavior and produce biological-inspired spiking patterns that match neuroscience known operations (1). Moreover,
neurons capable of full
quantum information processing through their
qubit states and
quantum trajectory provides capability for hybrid
quantum-classical operations through the level of coherence/
entanglement and non-Markovianity (2,3). These attributes further contribute to solving complex
quantum mechanical problems by providing a rich and diverse group for expressing
quantum neural states. Upgrading these hardware
neurons now with optical
spin qubits excitable with pulsed
laser excitation in the near infrared and designed from negatively charged silicon vacancies in
semiconductor silicon carbide (4) and Neodymium rare earth ions in the superconducting Niobium/Niobium
oxide film (5) that form the
memory provides access to the unique
spin Hamiltonian that considers electronic and
nuclear interactions. In this manuscript, we experimentally measure opto-electronic
quantum-classical
neurons integrated with a optical
spin qubit and examine how tailored neuronal spiking sequences drive the photoluminescence oscillations and modulate the
quantum spin transitions. We derive a
quantum model for the system that considers the interaction between the
neuron and optical
qubit spin and perform calculations to project how
quantum computing operations are expandable across the state space in the
quantum-classical
neuron and
spin qubit system. For example, the resulting impact on the
neuron quantum states where the strength is adjustable due to dynamical
memory changes. These results are critical for realizing hardware
neurons with
quantum optical capabilities and inspired by the existence in biology of biophotons.
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Quantum Physics
VQCSim: When Does Compile-Once Statevector Simulation Beat Generic Quantum Frameworks?
Anton Firc, Martin Perešíni, Vojtěch Mrázek et al. (+7 more)
Hybrid
quantum-classical machine learning workflows repeatedly evaluate many small parametrized
circuits during training and model exploration. In this regime, framework dispatch and orchestration overhead often dominate runtime. Prior simulators accelerate execution but leave open the question of when compile-once specialization is the right choice for static variational
circuits. We answer this question with VQCSim, a compile-once, PyTorch-native statevector execution path with native autograd. In a systematic MQT Bench study, VQCSim compiles all tested static
circuits and provides 87.7% end-to-end semantic validation. Across a five-GPU evaluation set, VQCSim delivers pooled median speedups of 4.49x for native inference and 26.78x for native training, while retaining a 3.31x advantage under matched finite-difference training. Ablation identifies native autograd as the dominant source of acceleration (27.6x), with compile-once caching and batch vectorization contributing additional gains. The speedup trades higher GPU
memory (VQCSim is
memory-limited at the high end) for lower runtime. We derive a hardware-aware regime map and release vqcsim-oracle, an open-source backend selector with 91.1%-97.7% top-1 agreement (including cross-GPU transfers), enabling automatic simulator selection in QML design loops.
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All authors Anton Firc, Martin Perešíni, Vojtěch Mrázek, Kamil Malinka, Vojtěch Staněk, Zbyněk Lička, Nouhaila Innan, Walid El Maouaki, Alberto Marchisio, Muhammad Shafique
Quantum Physics
On the Experimental Determination of Nonlocal Characteristics of Two-Qubit Gates
M. Karthick Selvan and S. Balakrishnan
In this paper, we discuss the experimental determination of the nonlocal characteristics of two-
qubit gates. Based on the recently derived expressions for the entangling power and gate typicality of two-
qubit gates, we construct two-
qubit quantum circuits to measure the entangling power and gate typicality of the two-
qubit gates, which are generated by the elements of the su(4) Cartan subalgebra. These elements describe the native interactions in many
quantum processors. Hence, these
circuits can be used to determine the nonlocal characteristics of native gates of many
quantum processors. In each
circuit, the native gate is applied twice. In addition, each
circuit consists of at least one CNOT gate. A set of six two-
qubit circuits is constructed to measure the entangling power. The number of
circuits is further reduced to three by increasing the nonlocal resources (the number of CNOT gates). To measure the gate typicality, a set of three two-
qubit circuits is constructed. Measurement of gate typicality requires more nonlocal resources than the measurement of entangling power.
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Quantum Physics
An efficient algorithm for approximate shadow Hamiltonian simulation
Abhijit Chakraborty, Bharath Sambasivam, Karunya Shirali et al. (+4 more)
We propose an efficient
algorithm based on shadow
Hamiltonian simulation to approximately simulate the real-time dynamics of observables under time-independent
Hamiltonians. Shadow
Hamiltonian simulation works at the level of the operator
algebra generated by the observables through commutators with the
Hamiltonian. Exactly encoding the
quantum state in this picture is generally inefficient for interacting systems due to the exponential growth of the operator
algebra. Our
algorithm overcomes this bottleneck by systematically identifying the elements of the
algebra most relevant to the target observables. This targeted approach is a controlled approximation that yields a highly efficient
quantum state encoding that substantially reduces the size of the
qubit register required to perform the time
evolution using the shadow
Hamiltonian. We propose two main
pruning schemes, one based on a predefined operator basis and another on a constructed Krylov basis. We also present a hybrid scheme that builds a Krylov basis within a pruned
algebra in the predefined basis. We
benchmark our
algorithm using
lattice spin systems in one and two dimensions, for both one- and higher-point correlators as observables.
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All authors Abhijit Chakraborty, Bharath Sambasivam, Karunya Shirali, Hunter Nelson, Mafalda Ramôa, Sophia E. Economou, Edwin Barnes
Quantum Physics
Paraparticles intrinsically exhibit Hardy-space breakdown
Kejun Liu
The
memory kernel of an open
quantum system obeys Kramers–Kronig (KK) relations if and only if its Laplace transform is analytic in the upper half-plane – a property known as Hardy-space analyticity. Here we show that non-
unitary exchange statistics, the defining property of paraparticles, intrinsically breaks Hardy-space analyticity. The metric $\eta$ that guarantees a real closed-system spectrum for these particles necessarily differs from the physical Born inner product ($\|\eta - I\|_F / \|I\|_F = 0.51$) – a mathematical consequence of the R-
matrix's non-unitarity, not a parameter choice. This metric is a "shadow metric": Schur's lemma forces it to commute with every bilinear observable, making the distortion physically invisible in the closed system. But when the paraparticle is coupled to a bath, any coupling operator that lies outside the
symmetry algebra – that is, any interaction that sees the internal flavour structure – exposes the distortion. The
memory kernel then develops upper-half-plane poles at coupling $g_c \approx 0.1$, breaking standard dispersion relations before the closed-system spectrum complexifies.
Fermions and
bosons, whose exchange is
unitary ($\eta = I$ as an analytic fact of the canonical anticommutation
algebra), are immune at any coupling, because there is no distortion to expose. The violation is intrinsic: it distinguishes non-
unitary exchange statistics from ordinary particle statistics at the level of the
memory kernel's analytic structure.
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Quantum Physics
Noise Resilience of Quantum Key Distribution Protocols Secured Against Independent Attacks With One-Way Communication
Adam Bílek, Ryszard Kukulski, Paulina Lewandowska et al. (+2 more)
We investigate the resilience to noise of single-
qubit quantum key distribution (QKD) protocols in the scenario of security against independent eavesdropping attacks and key
distillation based on one-way classical communication. To this end, we introduce a noise-based metric that quantifies the efficiency of QKD protocols. Within this framework, we analyze the maximal noise levels that allow Alice and Bob to asymptotically establish a secure secret key. Using this assumption, we compare the noise tolerance of general single-
qubit QKD protocols, in particular the BB84, B92, E91, and six-state protocols. Our main result determines the noise level threshold for QKD allowing one to distill an asymptotically secure secret key. Additionally, we demonstrate that the six-state protocol achieves the greatest resistance to noise while simultaneously yielding a higher post-selection efficiency than the other analyzed single-
qubit protocols, confirming its robustness within the considered security model. Finally, we perform an analysis of the proposed noise-based metric and the conventional
quantum bit error rate (QBER) metric.
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All authors Adam Bílek, Ryszard Kukulski, Paulina Lewandowska, Łukasz Pawela, Zbigniew Puchała
Quantum Physics
Trotter error compensation with polylogarithmic precision and nested-commutator scaling without ancillas
Xinzhao Wang, Shuo Zhou, Ziruo Wang et al. (+5 more)
Product formulas are among the most practical approaches to
Hamiltonian simulation, requiring no ancillary
qubits and exhibiting error bounds governed by nested commutators rather than only by
Hamiltonian norms. Their
circuit size, however, scales polynomially with the inverse precision. We develop a high-order nested-commutator compensation (HNCC)
algorithm that preserves the main advantages of product formulas while achieving polylogarithmic precision dependence in the
circuit size and the standard $\mathcal{O}(\varepsilon^{-2})$ sampling cost. HNCC uses a truncated Baker–Campbell–Hausdorff expansion to represent high-order Trotter errors by products of nested commutators and compensates these errors at the channel level through randomly sampled Pauli-rotation channels, avoiding Hadamard tests and ancillary
qubits. For a fixed $K$-th order product formula applied to a $k$-local
Hamiltonian on $N$
qubits with $\Gamma$ Pauli terms and local interaction strength $g_0$, HNCC estimates $\operatorname{tr}[Oe^{-i tH}\rho e^{i tH}]$ to additive precision $\varepsilon\|O\|$ using $\mathcal{O}(\varepsilon^{-2})$ repetitions. Its maximum gate count per
circuit is $\mathcal{O}\bigl( kN^{\frac{1}{2K+1}} \Gamma^{1-\frac{1}{2K+1}} \max\{\Gamma,N\log(1/\varepsilon)\}^{\frac{1}{2K+1}} (kg_0t\log(1/\varepsilon))^{1+\frac{1}{2K+1}} \bigr)$. Finite-size resource estimates for the periodic Heisenberg chain indicate that HNCC has the lowest estimated $T$-gate count per
circuit among the product-formula-based methods considered.
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All authors Xinzhao Wang, Shuo Zhou, Ziruo Wang, Pei Zeng, Jinzhao Sun, Qi Zhao, Tom Gur, Tongyang Li
Quantum Physics
Bounding Kirkwood-Dirac negativity of Gaussian processes
Luca Bianchi, Carlo Marconi, Riccardo Cioli et al. (+1 more)
The Kirkwood-Dirac quasiprobability provides an operational representation of a
quantum state, whose negativity serves as a measure of nonclassicality. Despite its fundamental importance, the extremal values of the Kirkwood-Dirac negativity are still unknown in the general case. We investigate the Kirkwood-Dirac quasiprobability of an arbitrary
quantum state under Gaussian processes. In this setting, we derive an upper bound on the negativity for any number of modes and measurements. For a single mode and two measurements, we show that the eigenstates of the quadrature operators saturate this upper bound, while a nontrivial minimum is reached by pure Gaussian states. As a consequence, our results indicate that Gaussian states are sufficient to achieve extreme values of nonclassicality.
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All authors Luca Bianchi, Carlo Marconi, Riccardo Cioli, Jan Sperling
Quantum Physics
Optimal tomography of bosonic and fermionic Gaussian states
Senrui Chen, Marco Fanizza, Filippo Girardi et al. (+4 more)
The sample complexity is the minimum number of copies required to learn an accurate classical description of a
quantum state. Bosonic and fermionic Gaussian
quantum states are families of
quantum states that play a key role in
quantum science and technology, from
quantum optics and many-body physics to
quantum chemistry,
quantum computing, and
quantum information theory. Despite their importance, their sample complexity had not been fully determined. We settle this open problem and show that both bosonic and fermionic Gaussian states can be learned using a number of copies that scales quadratically in the number of modes, regardless of whether the state is pure or mixed, and independently of any energy bound on the state. We derive these results by using the representation theory of Gaussian
unitaries and by putting forth a generalization of the random purification channel to this setting and beyond.
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All authors Senrui Chen, Marco Fanizza, Filippo Girardi, Ludovico Lami, Francesco Anna Mele, Michael Walter, Freek Witteveen
Quantum Physics
Optimal operating temperature for industry-compatible silicon spin quantum computing: colder is not necessarily better
Paul Steinacker, Amanda E. Seedhouse, Nard Dumoulin Stuyck et al. (+22 more)
Silicon
spin qubits are a leading candidate for large-scale
quantum computing owing to their compatibility with
semiconductor manufacturing. However, scaling to useful fault-tolerant processors will likely generate thermal loads that exceed the cooling power available at millikelvin temperatures. Raising the operating temperature eases cooling requirements but reduces gate fidelity, increasing the overhead of
quantum error correction. Identifying the operating temperature that minimizes total power consumption is therefore a key challenge for commercially viable
quantum computers. Here, we use gate set
tomography to
benchmark two-
qubit silicon chips fabricated in both industrial and academic environments over a range of temperatures. Elevated temperatures substantially shorten coherence times and increase gate and state-preparation-and-measurement infidelities. Based on these measurements, we develop a general power model for silicon
quantum computers that combines cryogenic cooling requirements with error-correction overheads. We show that a finite optimal operating temperature exists and is strongly influenced by a crossover temperature near 1 K in current devices, above which gate fidelity degrades rapidly. These results connect device-level fidelity limitations to system-level power requirements, providing design guidelines for large-scale silicon
quantum computers.
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All authors Paul Steinacker, Amanda E. Seedhouse, Nard Dumoulin Stuyck, Tuomo Tanttu, MengKe Feng, Santiago Serrano, Ensar Vahapoglu, Samuel K. Bartee, Philip Y. Mai, Alexis Shaw, Andreas Nickl, Sebastian Pauka, Brendan Harlech-Jones, Juan P. Dehollain, Fay E. Hudson, Kok Wai Chan, Thomas A. Ohki, David Reilly, Christopher C. Escott, Chih Hwan Yang, Wee Han Lim, Arne Laucht, Andre Saraiva, Andrew S. Dzurak, Jared H. Cole
Quantum Physics
Input-Aware Dynamic Backdoor Attack Against Quantum Neural Networks
Junrui Zhang, Zemin Chen, Lusi Li et al. (+3 more)
Quantum Neural Networks (QNNs) are a promising framework for
quantum machine learning on near-term
quantum devices, but their security risks remain insufficiently understood. Studies have shown that QNNs are vulnerable to
backdoor attacks, yet existing
quantum backdoors mostly rely on a fixed trigger shared by all poisoned inputs. This fixed-trigger design is a major weakness because many defenses detect or weaken the repeated patterns such triggers leave in data representations. Although input-aware dynamic
backdoors have been studied in classical neural networks, transferring them to QNNs is difficult because
quantum learning introduces new obstacles. In particular, measurement compresses the post-ansatz
quantum state into a limited classical output, weakening supervision for a trigger generator, while individual density
matrices fluctuate with the input and make per-sample contrastive learning unstable. To address these challenges, we propose Q-DIBA, the first input-aware dynamic
backdoor attack for QNNs. Q-DIBA jointly trains a classical trigger generator and a victim QNN through a three-mode mini-batch strategy that supports clean behavior, attack activation, and trigger specificity. To provide stable
quantum-level supervision, Q-DIBA introduces an ensemble density contrastive loss that operates on post-ansatz
quantum states before measurement and contrasts mode-averaged density
matrices rather than individual samples. Experiments on MNIST and Fashion-MNIST across multiple QNN architectures show that Q-DIBA achieves high clean accuracy, strong attack success, and high cross-trigger accuracy, demonstrating effectiveness, stealthiness, and input specificity. The attack also remains resilient against defenses including visual inspection, spectral-signature detection, and fine-tuning, suggesting that input-aware
quantum backdoors are an important threat to secure QNN deployment.
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All authors Junrui Zhang, Zemin Chen, Lusi Li, Mohammad Ghasemigol, Daniel Takabi, Rui Ning
Quantum Physics
Multiparameter Quantum Metrology in Molecular Dimers
Omar Bachain, Mohamed Amazioug and Rachid Ahl Laamara
We investigate multiparameter
quantum estimation in a molecular dimer composed of two dipole–dipole interacting two-level systems, focusing on the simultaneous estimation of temperature $T$ and detuning $\Lambda$. By employing a vectorization approach to derive the
quantum Fisher information
matrix, we analyze the precision limits of both simultaneous and individual estimation strategies. We show that simultaneous estimation outperforms the individual one in the near-resonant and low-temperature regime, where
quantum coherence is enhanced, while its advantage is progressively reduced under detuned conditions and increasing temperature. Our results demonstrate that temperature acts as a key control parameter governing both estimation precision providing a unified perspective on
quantum metrology. These findings highlight the potential of molecular
quantum systems as realistic platforms for multiparameter
quantum sensing.
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Quantum Physics
Quantum probe advantage in learning many-body systems
Wenzheng Dong, Andrew G. Green, Vlatko Vedral et al. (+1 more)
Which properties of a
quantum many-body system are operationally accessible is a central question underlying spectroscopy, thermodynamics, and
quantum information science. Conventional response theory answers this question within a system-only paradigm: one perturbs and measures the matter itself, obtaining susceptibility built from causally ordered nested commutators. Here we show that coherently controlled
quantum probes, when measured at the end, define a strictly larger operational learning framework beyond that accessible from response theory. We establish this through a
quantum-
circuit description that unifies spectroscopy, probe microscopy, and probe-based
quantum technologies within a common operational framework, from which we develop
quantum protocols for learning many-body properties from probe readout only. This advantage arises because the reduced dynamics of
quantum probes generically encode anti-commutator and mixed-order correlators of the target; therefore, measurements on the probe provide access to fluctuations, non-
equilibrium structure, and
entanglement entropy that are in general not accessible through response functions or a single probe alone. Moreover, we demonstrate that entangled probes can access many-body properties such as von Neumann
entropy. We prove that the required probe resources scale with the complexity of the target correlations rather than with the size of the many-body system.
Quantum probes are therefore not merely more sensitive sensors but provide a new way to learn many-body properties distinct from those of
tomography or
quantum simulation.
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All authors Wenzheng Dong, Andrew G. Green, Vlatko Vedral, Jinzhao Sun
Quantum Physics
Multiparameter Quantum Estimation in a Raman-Coupled Two-Qubit System
Omar Bachain, Mohamed Amazioug and Rachid Ahl Laamara
We investigate multiparameter
quantum estimation in a Raman-coupled two-
qubit system at thermal
equilibrium. Analytical expressions for the
quantum Fisher information
matrix are derived to characterize the simultaneous estimation of the temperature and Raman coupling strength. The corresponding
quantum Cramér–Rao bounds are obtained and compared with those of individual estimation strategies. Our results reveal optimal operating regimes determined by the interplay between thermal fluctuations and coherent interactions. In particular,
quantum thermometry exhibits a well-defined optimal temperature window, whereas the estimation of the Raman coupling strength is significantly enhanced in the low-temperature and weak-coupling regime. We further show that simultaneous estimation can outperform independent estimation within appropriate parameter regions, highlighting the advantages of multiparameter
quantum metrology. These results provide analytical insights into the ultimate precision limits of Raman-coupled two-
qubit systems and identify promising operating regimes for
quantum sensing and
quantum thermometry.
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Quantum Physics
Private Capacity of Quantum Channels Induced by Non-stabilizer Environmental States
Chunhe Xiong, Sunho Kim, Long Long et al. (+1 more)
We investigate the private capacity of
quantum channels using the recently proposed
quantum convolution theory for discrete-variable
quantum systems. We focus on the role of the magic resource played in this framework. Firstly, for a large class of convolutional channels, we find that the private capacity is zero if the fixed environmental state is a stabilizer state. Moreover, we show that the private capacity can be nonzero for some magic environmental states. Furthermore, we show that the private capacity of a discrete beam splitter
unitary is upper-bounded by the amount of magic of the environmental state. In addition, if the environmental state exhibits a certain symmetric structure, even if it is magic, the corresponding private capacity will also vanish for a class of convolution. These results emphasize the role of magic resources in
quantum communication
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All authors Chunhe Xiong, Sunho Kim, Long Long, Junde Wu
Quantum Physics
A new class of pure non-Gaussian quantum states
V.L.Gorshenin, B.N.Nougmanov, D.A.Chermoshentsev et al. (+2 more)
We discuss a new class of pure non-Gaussian
quantum states of light characterized by trigonal
symmetry on the phase plane. We propose the term “trigonal states” for them and show that they can be generated using the standard non-degenerate four-wave process supplemented by the subsequent heralding measurement of the
photon number in one of the two signal modes.
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All authors V.L.Gorshenin, B.N.Nougmanov, D.A.Chermoshentsev, I.A.Bilenko, F.Ya.Khalili
Quantum Physics · Cross-listed from physics.optics
Spacer-Mediated Gold Nanocube Arrays for Edge-Localized Excitonic Enhancement in Monolayer MoS2
Abdullah Efe Yildiz and Emre Ozan Polat
Plasmonic nanostructures offer an effective route for enhancing light-matter interaction in atomically thin
semiconductors, whose optical response is intrinsically limited by their sub-nanometer active thickness. Here, we numerically investigate excitonic enhancement in monolayer (ML) Molybdenum Disulfide (MoS2) coupled to size-tuned gold (Au) nanocube arrays separated by thin aluminum
oxide (Al2O3) and hexagonal boron nitride (h-BN) spacer layers. By varying the nanocube side length, the localized surface plasmon resonance is tuned across the visible spectral range to modulate the A- and B-excitonic transitions of monolayer MoS2. We show that the nanocube-size-dependent spectral
redshift can be further controlled through the spacer material and thickness, enabling systematic tuning of the near-field distribution, carrier generation rate,
quantum yield, and radiative decay enhancement. Localized plasmonic confinement yields excitation-rate enhancements of up to 4.35 at B-excitonic transition (605 nm) and 3.66 at A-excitonic transition (650 nm), while the radiative decay-rate enhancement exceeds 80, leading to 350-fold photoluminescence enhancement. Although both A- and B-excitonic channels are enhanced simultaneously, their relative contributions depend on nanocube size, spacer material, and spacer thickness, indicating wavelength-dependent excitonic modulation rather than strict
exciton-selective switching. These findings establish Au nanocube arrays as a simple, scalable, and tunable plasmonic platform for enhancing excitonic carrier generation and emission in ML MoS2.
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Quantum Physics
Operational Concealment of Measurement Incompatibility by Quantum Channels: Rank Loss versus Contraction
Mohd Asad Siddiqui and Zizhu Wang
Quantum measurements can remain incompatible yet become impossible to certify when all probe states first pass through a
quantum channel. We formulate this loss of certifiability as operational concealment and identify its exact finite-dimensional threshold. Under tomographically complete input access, a channel conceals some incompatible binary POVM pair if and only if its Heisenberg adjoint has nontrivial kernel. Thus, in this channel restricted single-use setting, rank loss rather than contraction is the universal transition for exact concealment: injective dissipative dynamics may render the effective measurements compatible while leaving exact concealment impossible. We quantify this distinction through a minimum-gain lower bound and show that regular time-local dynamics cannot produce exact concealment at finite time. We then classify all
qubit channels whose adjoint fibres admit a positive unital retraction, reducing concealment to ordinary joint measurability of canonical representatives. For orthogonal projected
qubit measurements we obtain an exact robustness formula and a strict separation from ordinary incompatibility robustness. Finally, quotient-space duality expresses this robustness as an experimentally accessible additive advantage in positive-payoff channel-output games. We also prove invariance under adjoining a passive finite-dimensional reference system for lifted target measurements, even when arbitrary joint compatible simulators are allowed on the enlarged output space. These results establish rank-sensitive criteria for certifying measurement incompatibility under restricted channel access.
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Quantum Physics
Higher-order covariance matrices for non-Gaussian quantum states
Vojtěch Kala, Petr Marek and Nicolas J. Cerf
Covariance
matrices lie at the heart of the powerful and well-established
symplectic framework for describing continuous-variable Gaussian
quantum states. However, since this framework only relies on first- and second-order moments, it is not sufficient for the analysis of non-Gaussian states because their higher-order moments are essential to capture some of their key properties. Here, we define higher-order covariance
matrices – more precisely, covariance
matrices built from higher-order quadrature monomials – which provide a simple way to evaluate the effect of Gaussian transformations on non-Gaussian states and can be used, for example, to address nonlinear squeezing or non-Gaussian nullifiers. Higher-order covariance
matrices can be estimated from homodyne measurement data using only a limited number of quadrature angles, which involves
matrices of moderate dimension compared with a full simulation in the Fock basis. The dimension of a higher-order covariance
matrix does not depend on the span of the
quantum states in Fock basis and, furthermore, scales only polynomially with the number of modes.
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Quantum Physics
Deploying and validating a metropolitan QKD secure network: architecture and field performance
Claudia De Lazzari, Nicola Biagi, Damiano Giani et al. (+15 more)
The advent of cryptographically relevant
quantum computers poses an existential threat to classical public-key infrastructure.
Quantum Key Distribution (QKD) addresses this challenge by providing information-theoretic security for key establishment, independently of any computational hardness assumption. In this work, the deployment and experimental validation of a metropolitan-scale
quantum-secure network between data centers in Milan is reported. The network operates over installed fiber infrastructure and implements a layered architecture integrating QKD hardware, standards-compliant Key Management (KM), and centralized Software-Defined Networking (SDN) orchestration. Dynamic path reconfiguration via active optical switching and trusted-node routing allow automated fail-over solutions. Application-layer validation across diverse protocols and workloads confirms the seamless interoperability of all system components. These results establish the technical and operational readiness of metropolitan QKD networks for production deployment, and offer a replicable blueprint for building
quantum-secure communication infrastructure at metropolitan scale.
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All authors Claudia De Lazzari, Nicola Biagi, Damiano Giani, Marco Russo, Fernando Chirici, Francesco Stocco, Saverio Francesconi, Giacomo Ferranti, Alessandro Soureal, Antonella Sanguineti, Bartolomeo Montrucchio, Christian Laurenzi, Oliviero Testa, Guglielmo Morgari, Antonio Manzalini, Tommaso Occhipinti, Alessandro Zavatta, Davide Bacco
Quantum Physics · Cross-listed from cond-mat.mes-hall
High-field Josephson effect enabled by a moiré Hofstadter spectrum
A. Díez-Carlón, M. Cárdenes Wuttig, N. Wei et al. (+7 more)
Magnetic fields generally suppress phase-coherent Josephson transport, limiting superconducting interferometry to relatively low fields. Here we show that moiré-engineered
graphene Josephson junctions can overcome this constraint. Using ballistic
graphene/hBN junctions, we establish phase-coherent Andreev transport through Fabry-Pérot oscillations and Fraunhofer interference that persist across both the primary Dirac cone and reconstructed moiré minibands. We then demonstrate phase-coherent Josephson interference up to 6 T in the fractal Hofstadter-butterfly regime, well beyond the range expected for conventional ballistic
graphene junctions. Comparison with Hofstadter-spectrum calculations reveals that superconductivity survives where the moiré potential transforms Landau levels with quenched group velocity into dispersive
magnetic Bloch bands with finite quasiparticle group velocity, enabling extended electron-hole Andreev trajectories across the junction. Our results show that Hofstadter minibands can stabilize phase-coherent superconductivity deep into the parameter domain conventionally associated with the
quantum Hall regime, establishing a new platform for high-field superconducting interferometry.
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All authors A. Díez-Carlón, M. Cárdenes Wuttig, N. Wei, D. Ivanov, P. Altpeter, P. Hakonen, K. Watanabe, T. Taniguchi, L. I. Glazman, D. K. Efetov
Quantum Physics
Interlocked Time Crystal in Coupled Spin-1/2 Ensembles under Local Dissipation
Zhen-Huan Yang, Zhen-Tao Liang and Dan-Bo Zhang
Multilevel dissipative systems can exploit multiple local transitions and coherence channels to generate nonstationary time-crystalline dynamics. Here we show that an analogous mechanism can be synthesized without enlarging the local
Hilbert space by coupling two locally pumped and decaying
spin-1/2 ensembles into a composite dissipative unit.Neither ensemble supports an autonomous oscillatory phase; instead, opposite pump-decay imbalances and inter-ensemble exchange coupling can lead to a single interlocked time
crystal with a fixed internal phase relation and no single-ensemble counterpart. The time-crystalline character is consistently established through the mean-field analysis, exact calulation of Liouvillian spectra at finite size, and temporal correlations with cumulant expansion. Our work establishes a route to dissipative time-crystalline order in which coupling between simple two-level subsystems generates the effective internal structure otherwise provided by multilevel constituents.
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Quantum Physics
Quantum Arithmetic Circuits in Public-Key Cryptography
Siyi Wang, Kyungbae Jang, Hyunji Kim et al. (+4 more)
Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack, including
quantum error-correcting codes and efficient
quantum algorithms. Among these,
quantum arithmetic
circuits serve as fundamental building blocks for various promising
algorithms. Despite their crucial role, the design of
quantum arithmetic
circuits faces challenges arising from the no-cloning
theorem,
qubit limitations, and
circuit depth constraints, which significantly impact the efficiency of large-scale
quantum computing. We provide an overview of
quantum arithmetic
circuits in the context of public-key cryptanalysis, with particular emphasis on optimization strategies such as measurement-based uncomputation and conditionally clean ancilla. We review state-of-the-art designs for essential arithmetic operations in public-key cryptanalysis such as addition, multiplication, and modular exponentiation. We also present an overview of the techniques used for fault-tolerant runtime and resource estimation in
quantum cryptanalysis. In brief, this chapter emphasizes strategies for designing resource-efficient
quantum arithmetic
circuits, providing a basis for realistic evaluations of
quantum cryptanalytic capabilities.
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All authors Siyi Wang, Kyungbae Jang, Hyunji Kim, Anik Basu Bhaumik, Anubhab Baksi, Hwajeong Seo, Anupam Chattopadhyay
Quantum Physics
Near-Optimal Mode Scaling for Finite-Dimensional Boson Sampling via Lie-Algebraic Leakage Bounds
Chon-Fai Kam and En-Jui Kuo
Boson sampling demonstrates
quantum advantage through the interference of indistinguishable particles, with output probabilities governed by
matrix permanents. Realizing it on deterministic, matter-based platforms requires encoding the bosonic modes in finite-dimensional local
Hilbert spaces, which introduces a leakage channel absent in linear optics: multi-particle bunching beyond the local truncation $d$. We develop a unified framework for non-interacting sampling on the irreducible representations of compact Lie groups, in which the transition amplitude is the immanant of a submatrix of the single-particle transition
matrix, recovering the permanent in the bosonic case. Within this framework we bound the bunching leakage through a Dyson-series analysis: decomposing the correlated many-body leakage operator into independent random
matrices and applying non-commutative concentration inequalities, we prove, in a Gaussian model of the transition
matrix, that its spectral norm concentrates at $\tilde{O}(\sqrt{n})$ rather than the $O(n)$ worst-case of prior
spin-based emulations; the passage to the physical Haar ensemble is reduced to a single submatrix-comparison input, verified at leading order. Exact numerics across local dimensions $d=2$–$5$ indicate that the bound is tight, the Haar-ensemble norm matching the closed form $\sqrt{d(n-d+1)}$ to sub-percent accuracy. This tightens the required mode number from $m=\Omega(n^4)$ to the near-optimal $m=\tilde{\Omega}(n^{1+2/(d-1)})$; for a
spin-1 representation ($d=3$) the overhead falls to $m=\tilde{\Omega}(n^2)$, matching the collision-free threshold. The result is independent of particle statistics and applies across finite-dimensional Lie-symmetric architectures, quantifying the spatial resources needed to preserve sampling hardness.
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Quantum Physics
$\mathtt{Q^2SAR}$: overcoming classical bottlenecks in drug discovery via quantum multiple kernel learning
Mariano Caruso, Daniel Ruiz, Alejandro Giraldo et al. (+1 more)
Quantitative Structure-Activity Relationship ($\mathtt{QSAR}$) modeling is a foundational computational methodology in early-stage drug discovery, heavily relied upon for predicting compound toxicity, bioavailability, and therapeutic potential. However, classical methods often struggle to effectively map the highly complex, non-linear, and high-dimensional interactions inherent in molecular data, leading to reduced predictive accuracy and costly late-stage clinical failures. In this paper, we present a
Quantum Multiple Kernel Learning ($\mathtt{QMKL}$) framework, dubbed Next-Gen $\mathtt{Q^2SAR}$, that leverages
Quantum Support Vector Machines ($\mathtt{QSVMs}$) to overcome these classical limitations. By encoding molecular descriptors into exponentially large
quantum Hilbert spaces, our approach substantially enhances the expressiveness of non-linear modeling. Benchmarking our
quantum-enhanced framework on a
dataset targeting the $\mathtt{DYRK1A}$ kinase (a critical target for Alzheimer's disease), the $\mathtt{QMKL}$-$\mathtt{SVM}$ achieves an impressive Area Under the Curve ($\mathtt{AUC}$) score of $0.8750$, significantly outperforming classical state-of-the-art Gradient Boosting models ($\mathtt{AUC} = 0.8037$). Furthermore, we establish a theoretical and empirical pathway toward resolving classical data bottlenecks through projected
quantum kernels ($\mathtt{PQK}$) and measurement accelerators. As
quantum computing architecture matures, this framework paves the way for autonomous cognitive architectures and self-improving drug discovery pipelines, promising to unlock deeper insights across vast chemical spaces and to accelerate the development of life-saving therapeutics.
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All authors Mariano Caruso, Daniel Ruiz, Alejandro Giraldo, Guido Bellomo
Quantum Physics
Multi-Stage Mamba-Based Architecture for Fast and Scalable Superconducting Qubit Readout
Luca Otting, Xiaorang Guo, Emmanouil Giortamis et al. (+3 more)
Reliable
qubit readout is a critical bottleneck toward fault-tolerant
quantum computing (FTQC). In superconducting
quantum processors, readout operations are both error-prone and high-latency. These challenges become more severe in frequency-multiplexed architectures, where signal crosstalk among neighboring
qubits significantly degrades readout fidelity. Existing machine learning (ML)-based approaches rely on feed-forward neural networks (FNNs) that suffer from large parameter sizes and lack an end-to-end network that jointly addresses relaxation errors and discriminates
qubit states. In this work, we present a multi-stage
qubit state discriminator based on the Mamba model, which enables efficient sequence modeling with linear complexity. The first stage performs initial state discrimination, followed by a refinement stage that identifies and mitigates relaxation-induced errors. Our lightweight model achieves a
geometric mean readout fidelity of 0.906, outperforming the best-reported state-of-the-art method while reducing parameter size by 49.6%; our optimal model further reaches 0.911. Both models remain robust across varying input trace lengths, maintaining a high fidelity of 0.893 at readout durations as short as 500 $ns$, achieving up to a 26% reduction in logical error rate over prior work in
quantum error correction (QEC).
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All authors Luca Otting, Xiaorang Guo, Emmanouil Giortamis, Benjamin Lienhard, Pramod Bhatotia, Martin Schulz
Quantum Physics · Cross-listed from cs.PL
The Time-Space Complexity of Checking Multiple Assertions in Quantum Programs
Shengyuan Yang and Charles Yuan
Runtime assertions are a promising mechanism for testing and debugging
quantum programs. But unlike the classical world, checking a
quantum program that contains multiple assertions often requires using additional space or running the program additional times. For example, on current
quantum hardware where mid-
circuit measurement is restricted or costly, an assertion's pass/fail outcome cannot be revealed immediately. Instead, it is routed into an ancilla
qubit during execution and read out by a terminal measurement. For a program with $n$ assertions, a naive strategy uses $n$ ancillas to learn all $n$ outcomes, while an alternative uses one ancilla but repeats program execution over $n$ rounds, checking one assertion per round. Both satisfy $S \cdot T = O(n)$, where $S$ is the number of ancillas and $T$ the number of executions: a fundamental time-space trade-off. Can one do asymptotically better? We reveal that the answer depends sharply on the information to be learned. Reporting the outcomes of all assertions requires linear complexity, but two partial-information tasks of detecting whether any assertion fails, and of identifying the first failing assertion, require only logarithmic complexity – an asymptotic improvement. Moreover, the checking strategies for these tasks can trade time for space in useful ways. In this work, we formalize the complexity of checking multiple assertions in a
quantum program. Using this definition, we establish its landscape of asymptotic lower bounds and constructive upper bounds. We confirm via a case study on Grover's
algorithm that the resource costs of constructed strategies match theoretical predictions, illustrating the practical design space for
quantum programmers.
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