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Friday 28 August

Quantum Physics · Cross-listed from cond-mat.mes-hall

Rapid Charge Stability Diagram Generation from Device-level Modeling of Semiconductor Quantum Dots

Ron Nodel, David W. Kanaar, Connor Nasseraddin et al. (+5 more)

Self-consistent Schrödinger-Poisson calculations are a powerful tool for predicting the behavior of layered semiconductor quantum dot devices. However, characterization of charge stability diagrams through fully simulated gate-voltage sweeps is computationally expensive. Combining a Multi-Domain Multi-Model (MDMM) approach with an automated tuning routine, we identify gate voltages associated with selected charge configurations. This small set of self-consistent simulations can be augmented with Full Configuration Interaction (FCI) energy calculations to extract charging energies, lever arms, and interdot Coulomb interactions to directly parameterize a Hubbard model for rapid charge stability diagram generation. For an Intel Tunnel Falls Si/SiGe device, we demonstrate the Hubbard model's ability to reproduce charge stability diagrams at a fraction of the computational cost in comparison to voltage bias sweeps. We further compare the simulated diagrams to experimental data and demonstrate qualitative agreement. Our result represents a step towards predictive digital twin models for semiconductor quantum dot devices. Finally, we apply this workflow towards lever arm engineering in a second device, demonstrating that the method extends to multiple architectures.
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All authors Ron Nodel, David W. Kanaar, Connor Nasseraddin, Tim J. Wilson, Hong-Wen Jiang, Jason R. Petta, Chris Anderson, Mark F. Gyure

Quantum Physics · Cross-listed from physics.optics

Quantum many-body effects in the optical response of ideal thin films

David Trejo-Garcia, Tapio T. Rantala, Marco Ornigotti et al. (+1 more)

We study quantum many-body effects in the long-wavelength optical response of confined electrons at finite temperatures. We simulate homogeneous electron gas confined in one dimension into a slab of nanoscale thickness. We demonstrate how the slab boundaries break down the ideal Drude response of free charge carriers, giving rise to scattering effects due to both the surfaces and quantum many-body interactions. We use a recent path-integral Monte Carlo (PIMC) approach developed in [Tiihonen et al. Phys. Rev. A 113, 053711] to quantify these effects in high accuracy. We perform phenomenological fits to Drude and Drude-Lorentz models parameters, manifesting various trends of the optical response with physical parameters like density and temperature, and numerical effects like finite size and the quantum statistics.
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All authors David Trejo-Garcia, Tapio T. Rantala, Marco Ornigotti, Juha Tiihonen

Quantum Physics

Role of the Drive in Mediating Correlations Between Two Qubits Through a Shared Dissipative Cavity

Nozhat Ghaseminezhad, Vahid Ameri and Alidad Askari

Using a numerically exact master equation, we demonstrate that two qubits, coupled solely through a shared damped, driven cavity, can become correlated. The drive influences both the amount and the type of correlation. For parametric, coherent, and resonantly modulated drives, the qubits develop quantum discord that increases with cavity temperature, while the logarithmic negativity remains numerically zero. This indicates the presence of discord without entanglement. In contrast, a time-modulated parametric drive is the only one that generates genuine two-qubit entanglement, achieving \(E_\mathcal{N} \simeq 0.15\) and concurrence \(\simeq 0.16\) at \((\eps, \gamma) = (0.3, 0.2)\), which rises to \(E_\mathcal{N} \simeq 0.32\) in the weak-coupling, moderate-damping region. Heating eventually destroys this entanglement around \(n_{\mathrm{th}} \simeq 0.2\), while discord continues to grow, resulting in a temperature-driven transition from entanglement to discord within a single drive. Moreover, the parametric drive offers the best protection for single-qubit coherence, unlike the coherent and modulated drives. An adiabatic-elimination model indicates that the cavity generates an effective coupling and a collective dephasing channel, both of which increase with temperature, explaining the observed discord without entanglement.
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Quantum Physics

Direct Adaptive Certification of High-Dimensional Entanglement with Bell Tests

Xu Kang Tan, Jesvita Menezes, Sanjan D. Murthy et al. (+1 more)

Entangled photons play a crucial role in quantum applications, and determining and characterising their entanglement is vital to using them effectively. High-dimensional entangled states offer richer possibilities, but their additional measurement degrees of freedom make them increasingly demanding to characterise. However, adaptive Bell-test methods based on complex simultaneous perturbation stochastic approximation (CSPSA) have so far focused mainly on qubits. Here we numerically investigate a Bell-inequality-violation-based method for detecting entanglement in unknown quantum states. We extend CSPSA to high-dimensional Bell testing by using the Collins-Gisin-Linden-Massar-Popescu (CGLMP) inequality for bipartite qudits. The resulting protocol can detect Bell-nonlocal correlations in unknown entangled states, whether pure or mixed, without first reconstructing their density matrix. Using 100 optimisation iterations in each of 100 independent finite-shot runs per number of dimensions d, we demonstrate certified CGLMP violations throughout d=2-8. For isotropic mixed states tested at a visibility of just 0.05 above the standard-Fourier violation threshold, we likewise observe confidence-certified CGLMP violations throughout the range of d studied. We compare this direct stochastic approach with quantum state tomography, the standard method for characterising an unknown state. In the matched benchmark, CSPSA uses fewer measurement configurations per attempt from d=6, whereas tomography requires fewer detected pairs per certified result through d=8. We also derive the phase dependence of the CGLMP parameter and clarify the features of its landscape that govern the adaptive search. Because the measurement-setting cost of each CSPSA iteration is independent of dimension, the method offers a particularly attractive route to the certification of high-dimensional entanglement.
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All authors Xu Kang Tan, Jesvita Menezes, Sanjan D. Murthy, Adetunmise C. Dada

Quantum Physics

Postselection-loophole-free Bell test under strict spacetime constraints

Kannan Vijayadharan, Matías Rubén Bolaños, Andrea Pompermaier et al. (+5 more)

Entanglement gives rise to correlations between distant quantum systems that cannot be explained by local realistic theories. Bell inequality violations provide a direct way to reveal these correlations and certify nonlocality, especially when the relevant experimental loopholes are closed. Time-bin encoding, in which quantum information is encoded into well-defined temporal modes, is a commonly used platform for distributing photonic entanglement in optical fibers. Yet loophole-free Bell tests with time-bin entanglement have received comparatively little attention, owing in part to the postselection loophole introduced by conventional interferometric measurements. Here, we demonstrate a fiber-based platform for Bell tests with time-bin entanglement that simultaneously closes the locality, freedom-of-choice, and postselection loopholes. We observe a CHSH violation of $S=2.583 \pm 0.002$, exceeding the local-realistic bound by over 265 standard deviations. Notably, this rigorous certification of nonlocality is achieved at a separation distance of $49.0 \pm 0.7$ m, substantially shorter than previous photonic Bell tests addressing comparable space-time constraints. Beyond its foundational significance, our results demonstrate time-bin entanglement as a viable route towards practical device-independent quantum communication and a future quantum internet.
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All authors Kannan Vijayadharan, Matías Rubén Bolaños, Andrea Pompermaier, Tommaso Bertapelle, Francesco B. L. Santagiustina, Costantino Agnesi, Giuseppe Vallone, Paolo Villoresi

Quantum Physics

A quantum generative model for in silico clinical trials using scarce training datasets

Olatz Sanz Larrarte, Reza Dastbasteh, Roberto Sanchez-Navarro et al. (+7 more)

In silico methods have emerged as a strategy to complement clinical trials. These are particularly relevant for rare or heterogeneous diseases for which traditional methods are costly or difficult to apply. While classical generative models have shown an extremely good ability to generate high fidelity data when trained using extensive databases, they often struggle when the available samples for training are scarce. In this work, we leverage the potential of quantum computers to represent complex probability distributions to generate high fidelity in silico patients. We propose a pipeline able to combine asymmetric databases into a quantum circuit that serves as a quantum generative model. We evaluate the efficacy of our proposal using a database of Myelodysplastic Syndrome (MDS) patients with 7 clinical variables as a proof-of-concept. We executed our quantum generative model in the IBM Heron r2 “ibm\_basquecountry” superconducting quantum computer and compare our method with well known classical baselines. Our results show that the quantum generative model surpasses the classical generative models in generalization and expressivity metrics, indicating its potential validity to generate high fidelity in silico patients for clinical trials.
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All authors Olatz Sanz Larrarte, Reza Dastbasteh, Roberto Sanchez-Navarro, Maria Diez-Campelo, Felipe Prosper, Ana Alfonso-Pierola, Mikel Hernaez, Sara Capponi, Pedro Crespo Bofill, Josu Etxezarreta Martinez

Quantum Physics · Cross-listed from cond-mat.quant-gas

Quantum thermodynamics near the border of a one-dimensional Bose gas

Carsten Henkel

We consider an ultracold Bose gas in a half-open potential well, otherwise confined to a quasi-one-dimensional geometry. The Bogoliubov equations for its elementary excitations are solved in the continuous spectrum to explore the particle and energy content near the edge of the gas, beyond the often applied local density approximation. In particular, gradients in the condensate density enhance density-dominated excitations in the border region. We discuss excess (missing) particles and their energy by comparing to suitable reference solutions for quasi-homogeneous systems. The density profile near the edge shows no Friedel oscillations, but a dipolar feature from the spill-out of thermally excited particles. The calculations are performed in the grand-canonical ensemble and in the thermodynamic limit.
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Quantum Physics

Engineering Coherence and Ergotropy through Spatial Arrangement of Environmental Channel in a Two-Qubit Quantum Battery

Gayatree Swain

We investigate how the spatial arrangement of environment channel influences the dynamics of coherence and work extraction in a two-qubit quantum battery with resonant qubits coupled through an XY-exchange interaction. Qubit B is attached to a finite-temperature thermal bath, while RTN noise is applied either to qubit A or to qubit B, depending on whether it is in a separated or co-located configuration, respectively. Two complementary product states are considered to initialise the coherence on different qubits. The dynamics are evaluated using local $l_{1}$-norm coherence, global ergotropy and the global-local ergotropy gap. The results suggest that a stronger exchange interaction enhances the redistribution of coherence without necessarily improving retention of extractable work. For the parameter investigated, the greater global ergotropy is retained in the case of the co-located configuration, especially when the initially coherent qubit is not directly affected by the RTN. However, the configuration provides the largest global-local ergotropy gap, which varies with the exchange interaction, initial state and thermal coupling. Suppression of the gap at large $J$ is typically observed in the case of stronger thermalisation, although enhancement of intermediate-coupling may occur. These results establish that total extractable work, local coherence and collective work advantage quantify the distinct aspects of quantum battery performances. The initial distribution of coherence and the spatial arrangement thus provide complementary mechanisms for regulating locally and collectively extractable work in interacting open quantum batteries.
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Quantum Physics · Cross-listed from physics.optics

Self-partitioned Interfacial Time Crystals

Joseph Huang and Yi Yang

Nonequilibrium many-body systems can spontaneously break symmetry in time, as in time crystals, or in space, through self-organized domains and interfaces. Whether these two forms of symmetry breaking can intertwine so that an emergent interface alone hosts time-crystalline order remains unknown. In this work, by introducing the Rabi-Hatano-Nelson model, we unveil the existence and mechanism of a self-partitioned interfacial time crystal (SPITC), where a homogeneous system generates its own internal and tunable interface, at which the time-translation symmetry is also spontaneously broken. Such a SPITC phase is intrinsically induced by nonreciprocity and open boundary conditions, without external pumping or long-range interaction. The periodic and open boundary phase diagrams of the system are both mapped out; vacuum and Dicke-like superradiance with static or active orders are identified, with analytical phase boundaries in the weak coupling limit. The frequency of the SPITC is found to scale quadratically with the spin-photon coupling strength, as we derive analytically for the slow dynamics of the spins. The position of the SPITC boundary scales with a critical exponent of $-1$ as a function of the degree of nonreciprocity, in stark contrast to $-1/2$ for an otherwise stationary boundary. Our construction of SPITC establishes a route to spatiotemporal order in non-Hermitian many-body systems.
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Quantum Physics · Cross-listed from cs.LG

Comparing Classical and Quantum Machine Learning for Regression in High Energy Physics Collision Data

Tariq Mahmood, Zain ul Abidin, Itzel Luviano Soto et al. (+1 more)

The classification and regression of particle collision events constitute a persistent computational challenge in experimental high energy physics, where large volumes of simulated data must be processed with both speed and precision. This work carries out a systematic comparison of four classical machine learning architectures, support vector machines (SVM), artificial neural networks (ANN), convolutional neural networks (CNN), and long short-term memory (LSTM) networks against their quantum counterparts: quantum SVM (QSVM), quantum neural networks (QNN), quantum CNN (QCNN), and quantum LSTM (QLSTM). All models are trained on simulated proton-proton collision events with electron-positron and muon-antimuon final states from the CERN Open Data portal, using transverse-momentum components as input features and transverse-momentum magnitude as the regression target. Classical architectures, and in particular the CNN and LSTM, achieve marginally better quantitative performance under current hardware and dataset constraints. Quantum models, however, reach competitive accuracy with substantially fewer trainable parameters: the QCNN reproduces the performance of the deep classical CNN using only four qubits and a circuit of depth three, pointing to a genuine parameter-efficiency advantage on near-term quantum devices. A baseline analysis confirms that the regression problem is non-trivial for shallow polynomial fits, supporting the relevance of the architectural comparison. These results characterize the trade-offs between classical and quantum approaches under realistic, resource-constrained conditions and provide a benchmark for future studies on actual quantum hardware.
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All authors Tariq Mahmood, Zain ul Abidin, Itzel Luviano Soto, Alfredo Raya

Quantum Physics · Cross-listed from hep-ph

Quantum computation of partonic Drell-Yan scattering cross sections and interference effects

Erik Bashore, Stefano Moretti and Timea Vitos

We probe the possibilities of efficiently constructing simple Feynman diagrams into quantum devices. More precisely, we study Drell-Yan lepton pair creation at the partonic level of the form q qbar -> gamma/Z -> l- l+. We develop quantum gates that build up the relevant diagrams using simple Feynman rules, such as vertex and propagator gates V and P. We show how the quantum circuit may compute simultaneous amplitudes in the phase space and how to reach the full integrated cross section from the outputs. In addition to this, we also show how the circuit is able to simultaneously isolate the interference effects of the contributing diagrams by a simple basis rotation. The circuit design is made to be general, and thus this work constitutes a step towards the implementation of arbitrary scattering process computations and efficient interference analyses.
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Quantum Physics

Physics-Constrained Conditional Generative Learning for Quantum State and Process Tomography

Daming Li

Quantum state and process tomography constitute essential diagnostic tools in quantum information science, yet their standard formulations suffer from prohibitive computational scaling as the number of qubits grows. In this work, we introduce a physics-constrained conditional generative adversarial network that bypasses iterative constrained inversion by directly learning a forward generative mapping conditioned on Pauli expectation values. The generator embeds a differentiable Cholesky layer at its output, which enforces Hermiticity, positive semidefiniteness, and unit trace by construction. Our experiments reveal that the strength of the $L^1$ penalty critically governs the emergence of GHZ coherence during training: an excessively large penalty postpones the coherence onset and yields a prolonged low-fidelity plateau, whereas an intermediate value enables the fastest stable convergence. Moreover, for high-temperature thermal states, an over-complete measurement basis proves necessary to prevent sustained late-stage fluctuations. By extending the same Cholesky constraint to the Choi-matrix representation, the framework naturally accommodates quantum process tomography. For systems with $n \ge 6$ qubits, the exponential growth of the underlying $2^n \times 2^n$ density matrix remains the fundamental bottleneck; we discuss how integrating tensor-network structures can contain the per-iteration cost while preserving reconstruction fidelity. Altogether, these results suggest that physically constrained generative learning offers a scalable and amortizable pathway toward data-driven tomography for noisy intermediate-scale quantum devices.
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Quantum Physics

Predicting Multipartite Entanglement in Quantum Circuits using Transformer

Darell Timothy Tarigan, Fadhil Fatih Shiddiq, Hadyan Luthfan Prihadi et al. (+5 more)

Multipartite entanglement is a critical property of parameterized quantum circuits (PQCs), particularly for near-term hybrid quantum-classical algorithms, as it characterizes their ability to generate highly entangled states. However, measuring entanglement remains computationally expensive because conventional Monte Carlo sampling scales unfavorably with system size. To overcome this challenge, we introduce a graph-based transformer surrogate that predicts both the first-order Meyer-Wallach measure ($Q_1$) and the second-order Scott measure ($Q_2$), resolving entanglement structures indistinguishable under $Q_1$ alone. Our central contribution is the qubit-interconnected graph (QIG) encoding for transformers, where each node represents a qubit and weighted adjacencies record entangling-gate multiplicities. Fused with a gate-level DAG encoder, this yields the QIG-Fusion model. Evaluated on 50,000 circuits spanning 4- to 8-qubit systems across a ten-seed protocol, QIG-Fusion achieves an RMSE as low as 0.037 ($Q_2$) and 0.038 ($Q_1$), with a Spearman rank correlation up to 0.95. This framework significantly reduces the computational cost of Quantum Architecture Search (QAS), enabling efficient entanglement estimation for large-scale PQCs.
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All authors Darell Timothy Tarigan, Fadhil Fatih Shiddiq, Hadyan Luthfan Prihadi, Donny Dwiputra, Jusak S. Kosasih, Yanoar P. Sarwono, Freddy Permana Zen, Rui-Qin Zhang

Quantum Physics

Pulsed single-photon magnetometry with a $\Lambda$-type three-level system: near-optimal frequency-resolved photon counting

Seyed Mostafa Moniri, Elnaz Darsheshdar and Mikayel Khanbekyan

We investigate pulsed single-photon magnetometry with a Zeeman-sensitive $\Lambda$-type three-level system driven by a classical control field. We derive the asymptotic output state and decompose its quantum Fisher information into photon-loss, spectral-intensity, and spectral-phase contributions. Environmental coupling reshapes the scattering response and can increase magnetic-field information. At critical coupling, real-frequency zeros of the scattering amplitude redistribute information toward measurable spectral intensity, allowing frequency-resolved photon counting to capture nearly all of the magnetic-field information encoded in the output state when the zeros lie within the pulse bandwidth. For long Gaussian pulses with a smooth, nonzero central-frequency scattering amplitude, the additional spectral-intensity contribution and residual spectral-phase information gap decrease as $T^{-2}$ or faster.
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Quantum Physics · Cross-listed from cond-mat.mes-hall

Quantum geometric bounds at finite temperature for one-dimensional chiral systems

Peng He, Hai-Tao Ding and Yu-Guo Liu

The geometry and topology of quantum states are intimately related at zero temperature through exact bounds that constrain geometric quantities from below by topological invariants. At finite-temperature, however, the analogous relations remain unclear. Here we establish rigorous geometric lower bounds for one-dimensional (1D) chiral-symmetric systems at finite temperature within the Uhlmann's framework for mixed states. We show that the Bures length is bounded by a continuous geometric phase angle. We further derive a temperature-dependent bound that interpolates between the zero-temperature limit and a trivial high-temperature regime. Our results are verified analytically and numerically using the Su-Schrieffer-Heeger (SSH) model and the spinless Kitaev chain model. Finally, we discuss potential ways to detect the geometry of the density matrix in quantum circuits, with the quantum imaginary time evolution (QITE) method.
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Quantum Physics

High-Throughput Normalized Min-Sum Belief Propagation Decoding for Quantum LDPC Codes with Near-Memory Processing

Jeonggeun Seo, Youngsun Han, Leanghok Hour et al. (+1 more)

Real-time quantum error correction requires classical decoders to process growing syndrome workloads with low and predictable latency. For quantum low-density parity-check (qLDPC) codes, iterative belief propagation (BP) repeatedly updates messages over sparse Tanner graphs, creating substantial memory-access and data-movement demands. We map normalized Min-Sum BP decoding of the [[144,12,12]] Bivariate Bicycle qLDPC code onto a DPU-based Processing-in-Memory (PIM) architecture. Within each DPU, 11 tasklets cooperatively decode one syndrome, while multiple DPUs process independent syndrome instances in parallel. Using uPIMulator and a data-qubit Pauli error model with ideal syndrome measurements, we compare throughput, per-syndrome processing time, logical error rate (LER), and single-syndrome tail latency against a 16-logical-CPU baseline. At a component-wise physical error probability of p=0.001 and one BP iteration, the projected aggregate kernel throughput of 2,560 DPUs reaches 1.071 x 10^7 decodes/s, compared with 1.22 x 10^6 decodes/s for the CPU, an 8.8x improvement. From two iterations onward, the measured LER remains below the physical error probability for every evaluated value of p. For one to five iterations, the maximum sampled serialized X+Z DPU compute latency remains below the 1 ms decoder-side reference for trapped-ion QEC, reaching approximately 0.873 ms at five iterations. These results show that near-memory processing can provide high aggregate throughput and sub-millisecond compute latency for qLDPC BP decoding under the evaluated conditions.
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All authors Jeonggeun Seo, Youngsun Han, Leanghok Hour, Dongmin Kim

Quantum Physics

From integrability to many-body quantum chaos through a Markovian bath

Xianlong Liu and Antonio M. García-García

Recent examples have confirmed the common belief that quantum chaos is always suppressed in the presence of an environment. Here we show that this is not always the case. We compute the Lyapunov exponent of a $q$-body Majorana Sachdev-Ye-Kitaev (SYK) model coupled to a Markovian bath. Provided that the jump operators describing the bath are isotropic random $k > 2$-body Majoranas fields, the Lyapunov exponent is positive for any strength of the coupling to the bath. Interestingly, this also applies to $q=2$ where the SYK is integrable which indicates that many-body quantum chaos can be induced by the environment. Moreover, for $q > 2$, where the unitary dynamics is quantum chaotic, and sufficiently large $k$, the Lyapunov exponent increases with the coupling to the bath. Explicit analytical results are obtained in the $q=2$ and large $q$ limits. Our results put forward an alternate route to induce and control the generation of scrambling in quantum many-body systems which is of potential relevance in the design of quantum information devices.
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Quantum Physics

Hybrid Heralded Noiseless Amplification with Finite-Cutoff Quantum Scissors

Haixi Miao and Timothy C. Ralph

A noiseless linear amplifier (NLA) can probabilistically amplify an optical state without the noise required by deterministic phase-insensitive amplification. We study a hybrid amplifier in which a finite-cutoff quantum-scissor NLA is placed between two single-mode squeezers. Analysis based on an ideal (infinite cutoff) NLA finds a gain enhancement from the squeezing. We explore the physics of this enhancement as the cutoff of the quantum scissors is increased. The low-cutoff sequence shows how this gain enhancement emerges from the truncated Fock space. Cutoff 3 is the lowest order at which the additional even- and odd-photon components can both contribute to gain enhancement, albeit with some skewing of the coefficients which reduces the fidelity. As the cutoff is increased the fidelity improves. However, unlike the ideal transformation, the finite-cutoff device depends on the phase of the coherent amplitude relative to the squeezing axes, with states aligned with the anti-squeezing requiring higher cutoffs to achieve high fidelity. We track behavior to high cutoffs and eventually see the performance predicted in the ideal theory emerge.
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Quantum Physics · Cross-listed from physics.comp-ph

Vectorized Symmetric and Fermionic Tensor Network Implementations for GPU-Accelerated Variational Monte Carlo

Si-Jing Du, Johnnie Gray, Ao Chen et al. (+1 more)

Variational Monte Carlo (VMC) calculations based on tensor networks (TN) have recently achieved competitive accuracy in ground-state calculations of strongly correlated spin and fermionic systems. However, existing tensor network VMC (TN-VMC) algorithms have not been formulated in a manner that can fully utilize GPU acceleration. We tackle the key missing ingredient, namely, the vectorized evaluation of tensor network amplitudes and tensor network operations. This ensures high GPU utilization by batching over computations with identical structure. In particular, we show how to achieve vectorization for the practically relevant case of abelian symmetric tensor networks (which includes fermionic tensor networks) by developing a “flat” tensor network formalism for block-sparse tensor representation and contraction. Using this, we construct a GPU-adapted symmetric TN-VMC workflow with batched tensor network computation. In the two-dimensional Fermi–Hubbard model, we demonstrate a GPU speedup of up to $300 \times$ over single core CPU implementations, for fermionic TN variational wavefunctions.
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All authors Si-Jing Du, Johnnie Gray, Ao Chen, Garnet Kin-Lic Chan

Thursday 27 August

Quantum Physics

Localizable Bipartite Rank-One Ideal Measurements Have a Block-Replicated Nice-Bell Structure

Ahmed Younis

We prove a complete structural characterization of finite-dimensional bipartite rank-one ideal projective measurements that are localizable without communication in the sense of Akibue and Miyazaki. Up to local-unitary equivalence, every such measurement basis is obtained by replicating a single nice Bell basis across equal-dimensional local subspace blocks. The necessity proof combines the causal block structure of complete measurements established by Beckman, Gottesman, Nielsen, and Preskill with their eigenstate-composition theorem for localizable superoperators. A reference block is first forced to be a nice Bell basis; the same theorem then propagates that basis consistently along every row, column, and interior block. The converse follows from the explicit localization protocol of Akibue and Miyazaki. This establishes their Conjecture 1 and gives a protocol-independent classification of bipartite rank-one ideal measurements in this setting.
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Quantum Physics

Every architecture of six two-qubit gates is locally universal on three qubits

Hyunho Cha and Jungwoo Lee

We present the first analytical determination of the exact accessible dimension for every fixed architecture of arbitrary two-qubit gates on three qubits. A support word represents which pair of qubits each two-qubit gate acts on, and its reduced length is obtained by merging consecutive gates on the same pair. If the reduced length is $r$, then the set of implementable three-qubit unitaries has accessible dimension $d(w)=\min\{63,9r+9\}$. Consequently, six arbitrary two-qubit gates are necessary and sufficient for local universality: every fixed architecture reaches a nonempty open subset of $\mathrm{SU}(8)$ when its reduced length is at least six. The result is stronger than existence of one favorable architecture. Every reduced six-slot support word is locally universal, including the alternating nearest-neighbor line $AB,BC,AB,BC,AB,BC$. The upper bound follows from a standard parameter-counting argument. The matching lower bounds are proved by Jacobian certificates in the Pauli basis. Up to qubit relabeling and reversal, there are $22$ reduced architectures of lengths two through six. For each one, a product of rational Pauli rotations yields a nonzero maximal minor modulo the prime $1{,}000{,}003$. Thus, any obstruction to global universality with six two-qubit gates must go beyond parameter counting, connectivity, and differential rank.
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Quantum Physics

Anticoncentration and entanglement in Gaussian boson sampling

Laura Shou, Adam Ehrenberg, Yu-Xin Wang et al. (+2 more)

Anticoncentration and entanglement are two properties used to study classical hardness or easiness of Gaussian boson sampling in varying regimes. In this paper, we consider three directions concerning anticoncentration and entanglement in Gaussian boson sampling: (1) We derive closed-form expressions for the second moment of hafnians of symmetric Gaussian products, and use this to precisely locate the anticoncentration transition as a function of the number of squeezed input modes. (2) We derive closed-form expressions for the Rényi-$\alpha$ Page curves for Gaussian boson sampling. (3) We study unequal input squeezing parameters $(s_i)_i$, and prove estimates as well as monotonicity of the average-case Rényi-2 entropy Page curve in terms of the magnitudes $|s_i|$, which allow for extending equal squeezing results to unequal squeezing.
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All authors Laura Shou, Adam Ehrenberg, Yu-Xin Wang, Joseph T. Iosue, Alexey V. Gorshkov

Quantum Physics

Scaling Alternating-Bias-Assisted Annealing for Precision Transmon Frequency Targeting on Superconducting Quantum Processors

Xiqiao Wang, Mark Field, Teng Zhang et al. (+18 more)

Recent advances in the alternating-bias-assisted annealing (ABAA) technique have successfully mitigated intrinsic Josephson-junction (JJ) fabrication variations. This new technique enables precision qubit frequency tuning alongside simplicity. However, it is critical to enhance tuning throughput and yield while investigating the factors that drive targeting performance as the technology scales. Here, we characterize ABAA tuning performance within a 150-mm wafer process flow and extend this technique to simultaneous, multi-channel tuning, demonstrating that a wafer-scale JJ resistance tuning precision of $\sigma=0.50\pm0.05\%$ alongside a component-level yield of $\ge 98.8\%$ can be achieved. Furthermore, we demonstrate a strong correlation between yield, tuning speed, and junction breakdown voltage, establishing the latter as a vital process control parameter for meeting production goals. Finally, we demonstrate a successful implementation of ABAA tuning on a quad-module quantum processor (Rigetti Cepheus-1-36Q), where we achieve an empirical frequency targeting precision of $\sigma \sim 30\text{ MHz}$ in both qubit and qubit-qubit detuning frequencies, contributing to high median two-qubit gate fidelities. These results confirm the efficacy and scalability of ABAA for high-precision Hamiltonian targeting, a critical enabler for modular superconducting quantum processor technology.
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All authors Xiqiao Wang, Mark Field, Teng Zhang, Xian Wu, Ferhat Aydinoglu, Joel Howard, Angela Q. Chen, Sara Elzeiny, Robert Smith, Timothy McSorley, Nicholas Sharac, Eyob Sete, Alysson Gold, Hilal Cansizoglu, Greg Stiehl, Josh Mutus, Kameshwar Yadavalli, Andrew Bestwick, Stefano Poletto, Raja Katta, David P. Pappas

Quantum Physics

Benchmarking Quantum Feature Encoding Strategies for Binary Classification with QSVM

Murat Kurt

The way in which classical data are encoded into quantum states plays a significant role in both classification performance and quantum circuit complexity in Quantum Machine Learning. In this study, the effects of different quantum feature encoding strategies on Quantum Support Vector Machine performance were investigated using five binary classification datasets. In particular, the statistical relationships between features were incorporated into quantum circuits through \(RY(\theta)\) and controlled-\(RY(\theta)\) gates, and this approach was compared with conventional quantum feature maps. The results demonstrate that incorporating statistical relationships into the encoding process can influence classification performance. However, more complex and densely entangled circuits do not necessarily yield higher performance. In addition, a composite evaluation metric was employed to jointly assess predictive performance, generalization, and circuit cost. The findings across the five datasets indicate that the choice of quantum feature encoding strategy should account for the underlying structure of the data and that predictive performance should be evaluated together with quantum circuit complexity.
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Quantum Physics

Error-Adaptive Quasi-local Decoding of the Toric Code

Hossein Dehghani, Sarang Gopalakrishnan and Michael Gullans

Topological quantum memories need decoders that are both reliable and scalable, but these goals compete: globally informed decoders are accurate near threshold yet expensive, while strictly local rules are fast but can miss long-range structure. Motivated by recent recoverability and mixed-state viewpoints, we make this tradeoff operational for the dephased toric code through a decoder-level local recoverability diagnostic. We compare global MWPM corrections to quasi-local corrections inside a target region and define a matching ratio $R_{\mathrm{match}}$, with mismatch $\epsilon_{\mathrm{match}}=1-R_{\mathrm{match}}$. Across geometry families, $\epsilon_{\mathrm{match}}$ shows strong buffer-controlled suppression and is well organized by a two-geometry scaling form. For scaled families, especially $a=b=d/8$, $R_{\mathrm{match}}$ exhibits a clear crossing and finite-size collapse near $p\!\sim\!0.09$, consistent with a growing recoverability scale near the decoding transition. We use this scaling to formulate an adaptive buffer-selection rule and to identify a distance-scaled initialization for a composite quasi-local RG decoder on the full torus. In the tuned family $a_0=b_0=d/8$, the resulting logical-failure curves show an apparent finite-size crossing at $p\simeq0.09$–$0.10$, below the conventional MWPM threshold scale. We focus on dephasing noise with perfect syndrome measurements to cleanly isolate the underlying behavior.
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Quantum Physics

Efficient Quantum Simulation of Variable-Coefficient Transport with Continuous Source Injection

Mohammad Mehedi Hasan Akash, Turag Dev, Nhat-Quang Nguyen et al. (+3 more)

Quantum time-marching algorithms for transport PDEs often represent variable coefficients and forcing through register-expanding dilations, block-encoding oracles, or repeated postselection. We present an alternative algorithm for a forced variable-coefficient advection-diffusion equation in flow-inspired skew-symmetric form that incorporates spatially varying velocity, viscous dissipation, and persistent source injection with a peak logical requirement of $n_q+1$ qubits. A centered skew-symmetric discretization makes the advection operator strictly skew-Hermitian for arbitrary velocity profiles, enabling an ancilla-free unitary realization using a Gray-code Trotter sequence of controlled-$R_y$ rotations. Diffusion is applied in the Fourier basis through a uniformly controlled rotation on one postselected ancilla, which is measured, reset, and reused between the two diffusion half-steps, while the source is incorporated classically through second-order Strang splitting. Statevector simulations for $N=16$ and $32$ recover second-order temporal convergence against high-accuracy classical solutions, while Richardson extrapolation gives fourth-order accuracy and reduces kernel calls by factors of four to fourteen. Independent tests through $N=256$ confirm second-order spatial consistency. We further show that the per-step ancilla failure probability is proportional to the instantaneous viscous dissipation rate, making postselection cost self-regulating over a fifty-fold viscosity range. Stable evolution is demonstrated for $5\times10^4$ time steps without observable secular error growth, while Gray-code advection accounts for $71$–$95\%$ of transpiled controlled-NOT gates. The fixed-width kernel provides a qubit-efficient building block for near-term hardware studies, although classical readout and state re-preparation remain the main obstacles to coherent multistep evolution.
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All authors Mohammad Mehedi Hasan Akash, Turag Dev, Nhat-Quang Nguyen, Yanzhu Chen, Huixuan Wu, Kourosh Shoele

Quantum Physics

Logical Neural Belief Propagation for Linear-Complexity Decoding of Surface Codes

Hee-Youl Kwak, Seong-Joon Park, Dae-Young Yun et al. (+2 more)

Quantum error correction (QEC) requires accurate and efficient decoders, yet belief propagation (BP), despite its linear decoding complexity, often provides insufficient logical accuracy on surface codes. We propose Logical Neural Belief Propagation (L-NBP), a BP-based neural decoder that redirects the decoding objective from physical-level to logical-level decoding. L-NBP uses a neural BP (NBP) module to produce posterior beliefs, which a logical classifier transforms into a continuous-valued soft syndrome for logical-operator prediction. Trained end-to-end by backpropagation, the NBP module learns soft syndromes that are favorable for logical classification. On surface codes, L-NBP matches or outperforms BP with ordered-statistics decoding (BP-OSD) and minimum-weight perfect matching (MWPM) while retaining the linear complexity of BP, and achieves a threshold of $17.5\%$ under depolarizing noise. Under circuit-level noise, L-NBP matches the accuracy of BP-OSD on the distance-$9$ surface code while requiring only $0.2\%$ of its complexity.
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All authors Hee-Youl Kwak, Seong-Joon Park, Dae-Young Yun, Eliya Nachmani, Jae-Won Kim

Quantum Physics

High-Dimensional Deterministic Secure Quantum Communication with Reed-Solomon Erasure Coding

L. F. A. de Sousa Moura, G. L. Zanin, P. H. Souto Ribeiro et al. (+1 more)

Deterministic Secure Quantum Communication (DSQC) is a quantum cryptographic technique engineered to transfer a message through a quantum channel, requiring an auxiliary classical channel for eavesdropping verification and decoding, but without prior key distribution. This article presents a theoretical high-dimensional prepare and measure DSQC protocol using the Reed-Solomon erasure coding to ensure data resilience to noise. This protocol offers the following benefits: it eliminates the need for quantum memory or entanglement, it can be built with commercially available technology, and its higher capacity improves the overall transmission rate.
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All authors L. F. A. de Sousa Moura, G. L. Zanin, P. H. Souto Ribeiro, C. Becker Westphall

Quantum Physics

Topological Winding Readout of an Emergent Page-Wootters Clock

Hesam Zaravashan, Gabriele Gradoni and Mohsen Khalily

The Page–Wootters construction gives time a Hilbert space, representing it as an internal degree of freedom whose readings the rest of the system evolves with respect to. We ask whether such a clock degree of freedom can carry a topological invariant, and we propose a photonic architecture in which it does and in which the invariant can be measured. Signal–idler pairs from spontaneous four-wave mixing in a coupled microring array supply the clock–system partition, with the idler occupying a Rice–Mele band whose staggered coupling and detuning are cycled adiabatically around a gap-closing point. One cycle acts on that band as a rigid translation by \(C\) unit cells, times a geometric phase periodic in the crystal momentum, times a dynamical phase, an identity exact in the adiabatic limit and independent of the state on which it acts. The readout targets the winding of that geometric phase across the Brillouin zone. Reversing the traversal of the pump loop cancels the dynamical phase and isolates twice the geometric phase in a two-photon coincidence fringe, while energy anticorrelation lets a filter on the signal scan the clock momentum without touching the clock and supplies the phase reference relationally, in place of an external optical reference. The estimate is protected on two independent levels, by the gap against smooth deformation and by the digital character of the unwrapping against noise below a threshold. A parameter budget anchored to thin-film lithium niobate places the requirements within reach at a conservative operating point.
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Quantum Physics

Machine Learning-Based Characterisation of the Non-Markovian Dynamics of a Nitrogen-Vacancy Centre

Tom Lannon, Mauro Paternostro, John Martin Gregg et al. (+1 more)

The interaction between a quantum system and its environment can be characterized by the spectral density function: knowing its structure is important for optimizing applications of quantum technologies such as quantum sensing protocols. In this work, we present the first experimental demonstration of a machine learning-based reconstruction of reaction-coordinate spectral density parameters from NV centre Rabi dynamics. Unlike the previous work, we recover all spectral density parameters rather than only the central frequency, and benchmark the performance of the neural network against the Cramér-Rao bound and maximum likelihood estimator. Our results demonstrate that the model predicted by the neural network can reliably reproduce the NV dynamics over the estimation window, and can produce estimates for some parameters with variances comparable to that of maximum likelihood.
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All authors Tom Lannon, Mauro Paternostro, John Martin Gregg, Amit Kumar