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Quantum control papers on arXiv, selected by a transparent rule and placed on the field map automatically. Search, filter by topic or year, or follow a topic's feed.
The 40 most recent papers.
Papers found
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Programmable Preparation of Topological Entangled States
Abstract
Programmable preparation of entangled quantum states is a central requirement for scalable quantum information processing, quantum networking and photonic quantum computing. Topological photonic platforms offer an attractive route towards robust quantum-state generation by encoding information in symmetry- protected optical modes, yet the generated entangled states are typically dictated by the lattice geometry and therefore lack programmability. Here we demonstrate programmable preparation of topological entangled states by inverse engineering the nonlinear optical pump profile of an integrated photonic lattice. Our approach enables deterministic control over both the dimensionality and modal structure of the generated entangled state while preserving its topological character. We experimentally realize silicon photonic topological superlattices in which the nonlinear generation pathway itself becomes programmable via tailored excitations. The superlattices host a multiband manifold of co localized topological interface modes, while coherently controlled inputs synthesize pump superpositions within this protected basis. We showcase this principle by selectively addressing topological biphoton eigenstates, steering correlations to produce a desired target state in a high-dimensional Hilbert space, and inverse-designing pump states that generate targeted Schmidt dimensionalities. Site-resolved two-photon correlation measurements remain reproducible across nominally identical fabricated devices, demonstrating robustness to realistic nanofabrication-induced disorder. Programmable preparation of topological entangled states establishes a pathway towards exploiting topological photonic modes as application-specific quantum resources, enabling tailored input states for high-dimensional quantum communication, quantum networking and photonic quantum computing.
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Programmable all-to-all entangling gates for cavity-coupled atoms
Abstract
Fault tolerant quantum computers greatly benefit from having both high fidelity entangling gates and a non-local qubit connectivity. However, most entangling gates for neutral atoms are local, requiring separated atoms to be moved using optical tweezers to yield entanglement between them. Here, we design a high fidelity Mølmer Sørensen-like entangling gate between neutral atoms coupled to a photonic cavity, enabling a programmable all-to-all connectivity through the shared cavity coupling. The gate is both robust to changes in cavity photon number, and enables selective entanglement between any subset of separated atoms through local laser addressing. This eliminates the need to physically move atoms to perform the gate, and therefore motional errors and erasure are suppressed. Using experimentally realistic parameters we demonstrate gate fidelities exceeding $F > 0.99$, with higher fidelities achievable through optimal control of the pump amplitudes.
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Quantum control of solid state qubits via Reinforcement Learning
Abstract
The use of reinforcement learning (RL) in the design of quantum control strategies for pulse level control of NISQ era quantum devices is attracting growing interest. Model-free RL, not requiring preexisting knowledge of the physical system, acts as a black-box optimization tool well suited for noisy devices. In this work, we provide a simulation-based analysis of the performance of model-free RL for state preparation and qubit gate design in a challenging setup: indirect control of NV nuclear spins in a spin-bath. In particular, the spin-bath is modeled via the generalized cluster correlation expansion accounting for magnetic impurities and intra-bath interactions. We analyze the performance of the RL agents by performing simulations with minimally observable environments and noisy, sparse rewards as introduced in (Phys. Rev. X 12, 011059), and compare them to other state-of-the-art black-box optimization tools.
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Time-optimal robust quantum control for partially known errors
Abstract
Robust quantum control usually assumes one of two extremes: the error is of a known form and only its strength is unknown, or nothing at all is known about it. In practice one often sits in between. The size of a static error is unknown, but its class is known, for example, it only shifts energy levels, or it acts on each subsystem separately. We ask how fast a control can cancel, to first order, every error in such a class. A time-independent Hamiltonian can do this if and only if all errors in the class have zero diagonal in a common basis. In that case an equally spaced energy ladder in this basis does it after one period. A lower bound that holds for any time-dependent control with bounded drive power shows that this simple constant control is optimal for several natural classes, including unknown level shifts and unknown local errors on two subsystems. Completely unknown errors need a time-dependent control, and there, knowing the error class shortens the minimum time by a factor $\sqrt{d^2+1}$. So partial knowledge of the error changes not only how long an optimal robust control takes, but also its form.
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Reducing the Cost of Qudit State Preparation by Learning a Sparse Structure for SNAP Gates
Abstract
Preparing quantum states in bosonic qudits with SNAP--Displacement sequences requires both optimizing the gate parameters and deciding which Fock levels should be controlled by each SNAP gate. A fully parameterized ansatz assigns an independent phase to every Fock level in every gate, leading to a number of phases that grows steeply. This constitutes a problem for short to medium term systems as controlling many phases requires complex control pulses which are subject to increased control errors. Previous work reduced this cost by restricting the trainable phases to predefined sparse patterns, such as a diagonal or a grid, which however may not be optimal for a specific target state. In this work, we address this limitation by introducing a method that learns which phases are needed together with their values, using a differentiable mask. A sparsity penalty encourages the removal of unnecessary phases, while temperature annealing gradually turns the masks into binary decisions. We compare the proposed method with fully parameterized and predefined sparse ansatzes on Fourier and Haar-random target states. The evaluation considers both the minimum number of phases required to reach different infidelity thresholds and the overall trade-off between fidelity and phases required, measured through Pareto frontiers and hypervolume. The results show that learning the location of the phases together with their values provides competitive or improved fidelity--resource trade-offs, although the advantage depends on the target state and qudit dimension.
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Agent-assisted experimental strategy transfer across quantum processors
Abstract
Progress in quantum hardware requires a growing volume of experiments across diverse devices, straining the capacity of human experts. Automation remains challenging because device differences and drift can render workflows developed on one processor unsuitable for another. Here we present an agent-assisted experimental strategy for conducting experiments across three-qubit nuclear magnetic resonance processors. Developed on one processor and applied sequentially to four others, the strategy uses an agent to assess experimental evidence, select subsequent measurements and adapt procedures, with operators providing instrument preparation and physical intervention. Using three-qubit Grover state preparation as a common task, each deployment combined device-specific calibration, control-pulse optimization and measurement. The experimental strategy was refined through sequential deployment, and all four processors ultimately produced outputs dominated by their respective marked states. The marked-state populations of the reconstructed dominant eigenstates ranged from \(0.910\) to \(0.959\), with relative deviations below \(3.8\%\) from the ideal value of 0.945. These results demonstrate that an agent-assisted experimental strategy can be reused and refined across processors to realize a common quantum task, providing a basis for scaling experimental practice beyond individual devices.
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Dynamical Decoupling of Nonclassical States in a Biased-Noise Spin Qudit
Abstract
Encoding quantum information in $d$-dimensional systems (qudits) with $d>2$ offers appealing new directions for resource-efficient quantum computing. However, protecting the coherence of nonclassical qudit resource states remains an open challenge. Dynamical decoupling (DD) is a well-established technique for extending coherence, but its application to qudits is hindered by the quadratic scaling of the decoupling sequence overhead with the dimension $d$. As a result, demonstrations of qudit DD have so far been limited to low-dimensional qudits. Here, we show that noise-biased qudits enable a nontrivial reduction of this overhead, for example, from quadratic to linear. We perform qudit DD on a model $d=8$ qudit, the nuclear spin of an antimony donor in silicon. We benchmark DD performance on highly nonclassical states such as uniform superpositions, cat states, and Haar random states and measure coherence improvements up to a factor $5$ to $10$. For a spin-cat error correction code, continuous DD extends the coherence time of the logical superposition $|+\rangle_L$ to $225$~ms, compared to $19$~ms under free evolution and $85$~ms with a Hahn echo. This improvement shows that DD sequences tailored to a system's noise bias can significantly enhance the lifetime of encoded logical qubits.
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Deterministic and programmable generation of mechanical multipartite entangled states
Abstract
Multimode mechanical resonators offer a large set of densely packed, long-lived bosonic modes within a single compact device, making them attractive for quantum simulation, quantum information processing, and quantum-enhanced sensing. Many such applications rely on multipartite entanglement, yet deterministic mechanical entanglement has so far been largely limited to pairs of modes. Here we demonstrate the deterministic and programmable preparation of multipartite entangled states among the phonon modes of a high-overtone bulk acoustic wave resonator coupled to a superconducting transmon qubit. By sequentially applying optimal-control-engineered isometries between the qubit and successive modes, we generate matrix product states of bond dimension two, including $W$, Greenberger-Horne-Zeilinger (GHZ), and cluster states. We fully characterize these states via quantum state tomography and certify genuine multipartite entanglement among up to four modes. We further demonstrate correlated-noise sensing by exploiting the complementary decoherence responses of the stored $W$ and GHZ states, isolating inter-mode phase correlations from local decoherence and placing quantitative bounds on collective dephasing. Our results establish a scalable approach to preparing multipartite entangled states in mechanical systems, with promising applications in multiparameter sensing and tests of quantum mechanics with massive objects.
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Quantum-enhanced mechanical sensing with machine-learning estimation
Abstract
Massive mechanical oscillators couple directly to forces, accelerations and gravity, making them attractive probes of new physics and of quantum mechanics at macroscopic scales. Pushing sensitivities beyond the standard quantum limit for signals of unknown phase requires non-Gaussian quantum states, whose metrological advantage has so far been confined to lighter systems such as trapped ions. Here we operate a microgram-scale acoustic mode of a high-overtone bulk acoustic wave resonator as a phase-insensitive quantum-enhanced sensor. A transmon qubit prepares the mode in Fock states of up to seven phonons by optimal control, and resolves its phonon-number distribution after interaction with a weak resonant signal. Bayesian analysis yields a Fisher information five times the vacuum value, a 7.0 dB gain in signal-amplitude sensitivity over any classical probe state, irrespective of its energy, currently limited by state preparation infidelities. We then train a neural network on the measured sensor response to perform Bayesian estimation without any analytical model of the system, showing the same sensitivity gain with half the systematic bias. Our results establish acoustic resonators prepared in non-Gaussian states as quantum-enhanced probes for high-frequency gravitational waves, dark matter and wave-function collapse.
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Principles and Techniques for Agentic Research in Experimental Physics
Abstract
The use of artificial intelligence (AI) in physics research is increasingly common, yet few guidelines exist for its effective use. Starting with a principles-based approach, we outline a set of ten requirements for collaborative AI agents in experimental physics, spanning scientific norms, effective agent use, and domain expertise. We take a human-centered approach in which agents act as collaborators that amplify rather than replace the expertise of a human researcher (user) who directs the work and is responsible for its results. We then present a framework designed to enforce these requirements, detailing methods for improving off-the-shelf behavior of large language models (LLMs) with custom scaffolding and describing general-purpose scientific workflows and skills. In particular, we highlight the power of closed-loop campaigns where agents work iteratively toward a well-defined goal. We demonstrate the potential of this mode of research through six case studies in experimental physics, covering device design, hardware control, neural network optimization, physical model identification, and data analysis. All six case studies result in useful work products that add utility to our research, including a neural network architecture and solid-state quantum defect photodynamic model that substantially outperform our published work; a microwave waveguide design that extends a published design concept to a fabrication-ready device meeting our experimental constraints; a quantum control pulse sequence candidate that improves simulated performance by more than an order of magnitude; commissioning of an NMR spectrometer to $\sim$1~Hz frequency precision on live hardware; and finally a data-fitting pipeline that achieves, to our knowledge, the first reconstruction of the Ising microstate of an artificial spin-ice array from diffraction-limited magnetic imaging.
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Architecting Instruction Execution for Scalable Fault-Tolerant Quantum Computing
Abstract
Scaling fault-tolerant quantum computing (FTQC) requires orchestrating millions of operations continuously across a tightly coupled classical-quantum control stack. A critical challenge in this orchestration is determining the optimal hardware-software boundary, i.e., the Quantum Instruction Set Architecture (QISA). We focus on cryogenic, fixed-connectivity qubit platforms, such as superconducting and topological Majorana qubits. For these, existing QISA choices either operate at too low a level, violating cryogenic thermal budgets at scale, or at too high a level, imposing unrealizable complexity on the control engine. To reason about these tradeoffs, we introduce the ARIES instruction set hierarchy, which categorizes QISAs into distinct abstraction levels. To systematically evaluate these levels, we develop an end-to-end evaluation toolflow featuring a cycle-accurate classical driver and hardware engine simulator. Using eight quantum applications across superconducting and topological qubit platforms, we measure instruction bandwidth, transceiver power dissipation, and measurement processing overheads. We demonstrate that while physical-level abstractions exceed the thermal limits of dilution refrigerators by orders of magnitude, canonical-level abstractions significantly underestimate hardware routing congestion and execution runtimes. Our Level 4 QISA (local logical operations) offers an optimal architectural balance. As quantum hardware platforms scale toward FTQC in the coming years, our findings provide concrete architectural guidance for the design of their classical control stacks and instruction interfaces.
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Geodesic steering for rapid dissipative entanglement distribution
Abstract
We describe an optimal-control strategy designed to accelerate the dissipative preparation of complex, highly entangled quantum many-body states. Analogous to optimal steering of isolated quantum systems, our scheme identifies control pulses that guide the evolution of open quantum systems along trajectories of instantaneous steady states while minimizing leakage resulting from non-adiabatic transitions. In many cases of interest, these control parameters can be derived analytically and without the need for computationally expensive numerical simulations of the full many-body master equation. We apply this technique for the preparation of bi- and multipartite entangled states in qubit systems coupled to a common photonic waveguide or a distributed squeezed reservoir. In both scenarios, our optimal-control strategy significantly outperforms the bare relaxation dynamics after a quench, reducing preparation times of near-maximally entangled states by orders of magnitude. This drastic speedup makes dissipative entanglement distribution protocols compatible with high-fidelity quantum information processing applications and illustrates more broadly the potential of leakage minimization for accelerating reservoir-engineering schemes.
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Scalable Exact Non-Pauli Noise Simulation for Fault-Tolerant Quantum Circuits
Abstract
Fault-tolerant quantum design relies on simulating noisy quantum error correction (QEC) circuits with hundreds to thousands of physical qubits and large circuit depths. High-throughput stabilizer simulators, such as Stim, are the de facto tools for this regime. However, these simulators typically support only Clifford gates and stochastic Pauli noise. As a result, more realistic device noise models-such as coherent control errors and thermal relaxation-are often approximated using Pauli Twirling. This replacement offers speed but can introduce inaccuracies. To address this, we propose QuasiStim for scalable exact QEC simulation of realistic noise, with QuasiFold as a compiler frontend and DeltaFrame as a sampling backend. QuasiFold lowers sampling overhead by merging equivalent non-Pauli sites in the quantum circuit. DeltaFrame samples the resulting stabilizer trajectories by reusing precomputed predicted references instead of resimulating the full tableau for each shot. QuasiFold can reduce the number of shots by over $100\times$ on bivariate-bicycle (BB) codes. Compared to a per-shot tableau simulator, DeltaFrame is $166\times$--$1331\times$ faster on rotated surface-code memory under coherent $R_Z$ noise as $d$ grows from 5 to 35. QuasiStim also makes the PTA bias measurable: the gap is non-negligible and varies with noise strength, decoder, and circuit schedule. QuasiStim will be open-sourced upon publication at https://github.com/isaachyw/QuasiStim
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Molecular Vibronic Complexity as a Quantum Resource for Optimal Control: Nonadiabatic Mixing Creates Protected Coherence Subspaces in Dissipative Environments
Abstract
In molecules, electronic coherence typically decays within a few hundred femtoseconds, a timescale usually attributed to the environment. We show that it is set to a large extent by which coherences are excited: the molecule can host coherences that the bath barely sees, and optimal control can find and exploit them. Using gradient-based optimal control (GRAPE) with Redfield dynamics, we maximize the total vibronic coherence between the electronic ground and an optically bright electronic excited state in a three-state model with nonadiabatic features, in two regimes of low and high nonadiabatic mixing and for different system-bath coupling strengths. The Liouvillian spectrum reveals, in both regimes, a well-separated coherence mode with substantial ground-bright character that decays on a picosecond timescale. This mode is protected by mixing with the dark state, which brings the geometry of the optically accessible excited state close to that of the ground state and thus weakens its coupling to the bath. Without prior information, GRAPE finds this mode and keeps the photoexcited wave packet near the Franck-Condon region. At equal fluence, it increases the coherence at 800 fs by more than two orders of magnitude over a Gaussian pulse at the weakest coupling, and by many more at stronger coupling. The Liouvillian predicts the bath dependence of the long-lived coherence to within 1\%, and a Gaussian pulse tuned to the mode frequency comes within 10\% of the best pulse found. Beyond two-level and spin systems, our study puts forward the vibronic structure of molecules as a route to protected coherence subspaces, identifying a dark-state protection mechanism and a design criterion based on molecular parameters. These results lay the groundwork for our goal of using vibronic molecular systems as a resource for long-lived, controllable coherences in molecular quantum information science.
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Proposal for a multi-ion optical clock with hundreds of ions
Abstract
Scaling trapped-ion optical clocks to hundreds of ions remains a major challenge due to inhomogeneous frequency shifts in large ion crystals. Here, we propose a circular surface-trap architecture for a multi-ion optical clock with hundreds of ions. The rotational symmetry of the ion crystal suppresses the main sources of inhomogeneity, quadrupole shift.We investigate the feasibility of a clock based on a ring crystal of 400 $^{40}\mathrm{Ca}^{+}$ ions and propose a suitable experimental setup configuration. We have shown that circular configuration of ions leads to suppression by two orders of magnitude of the quadrupole shift comparing to the linear trap. Combined with stray-field compensation and dynamical decoupling techniques, this architecture provides a pathway toward multi-ion optical clocks with fractional frequency uncertainty at the $10^{-18}$ level and an expected 20-fold improvement in frequency stability compared to single ion clocks.
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Entanglement detection in dynamical quantum systems
Abstract
Quantum science and engineering increasingly target the exploitation and control of large-scale dynamical systems. As system size grows, novel phenomena and quantum advantages emerge, but the resulting many-body dynamics become correspondingly harder to monitor and characterize. In particular, the underlying Hamiltonian often lacks symmetries, and the induced many-body dynamics quickly become hard to track. Focusing on one of the most important quantum features---entanglement---we demonstrate that, for a broad class of common Hamiltonian models, one can design effective witnesses that detect both the presence and structure of entanglement over relatively long evolution times. Inspired by stabilizer-based simulation, we track the evolution of generalized stabilizers of the underlying state and use them to construct linear entanglement witnesses. Through numerical experiments on Heisenberg-type Hamiltonians with up to twelve qubits, we show that the required number of measurement settings can be kept at a modest scale as the system size increases, and entanglement detection remains effective over evolution times that significantly exceed those accessible to naive approaches. The corresponding calculations can be carried out largely symbolically. Furthermore, unlike accurate state simulation, the stabilizer-based design of entanglement witnesses can be performed in a much more coarse-grained, digitized manner. We hope these results will stimulate further exploration of the quantum control of large systems.
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A complete classification of operator controllability for closed three-level quantum systems driven by a single control
Abstract
In this work, we study operator controllability of finite-dimensional closed quantum systems driven by a single coherent control. Two general Lie-algebraic results on controllability of such systems are proved. The first gives sufficient conditions under which controllability of the system is preserved when controlled energy-level shifts are added. The second gives a sufficient basis-element condition under which the dynamical Lie algebra contains $\mathfrak{su}(N)$ and the system is therefore operator controllable. These results, together with known controllability conditions, are applied to obtain a complete classification of operator controllability of all three-level quantum systems in terms of their free and interaction Hamiltonian matrix elements. This classification covers all combinations of energy-level and level-spacing degeneracies, two or three allowed transitions, as well as the presence or absence of controlled energy-level shifts, and gives necessary and sufficient conditions for operator controllability in each case.
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Fast continuous ion transport through X-junctions with low motional excitation for QCCD architectures
Abstract
Trapped ion quantum computing based on the quantum charge coupled device (QCCD) architecture uses functional zoning and ion transport to enable high fidelity computation and all to all qubit connectivity. As trapped ion quantum processing units (QPU) scale, 90° X-junction turns account for an increasing fraction of total transport time. Frequent junction crossings, therefore, make transport speed and final phonon excitation direct determinants of quantum algorithm execution efficiency. However, complex electric fields in X-junctions complicate waveform design, making it difficult to achieve high speed and low final phonon excitation simultaneously. Here, we develop a waveform design method for low-phonon-excitation high-speed X-junction(LHX-T) transport. It integrates low barrier pseudopotential channel design using multiple radio frequency (Multi-RF), multidimensional shortcut to adiabaticity dynamics, and constrained DC voltage optimization over the entire transport sequence. This framework connects waveform design, control, and computational validation, with smooth multichannel waveforms computed rapidly through a Karush-Kuhn-Tucker(KKT) linear system. The resulting waveform transports a single $^{171}Yb^+$ ion through a 90° turn in $5μs$ at an average speed of 14.6 m/s. Over 50 consecutive round trips, the final equivalent coherent phonon number consistently stays below 0.001, with no noticeable accumulation over time. System level evaluations at the QCCD scale show that the median duration of a single execution cycle is reduced by about $30\%$ across various circuit types. The fraction of execution time spent on transport decreases from approximately $70\%$ to $55\%$. This approach offers a means of designing fast ion transport waveforms with low phonon excitation for scalable QCCD based QPUs and provides a technical basis for efficient execution of quantum algorithms.
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Electric-dipole-induced nuclear electric resonance in silicon
Abstract
The nuclear spin of a phosphorus atom in silicon is considered as a promising quantum information carrier for quantum computing due to its long coherence time. Coherent control of the nuclear spin is typically realized using nuclear magnetic resonance (NMR). In this work, we theoretically propose that with the aid of hyperfine interactions and magnetic field gradients, fast electric-dipole-induced nuclear electric resonance (EDNER) can be achieved. The stronger EDNER (compared with NMR) arises from the combined effects of hyperfine interaction between the nuclear and electron spins and coupling between the electron spin and charge degrees of freedom mediated by magnetic field gradients in this scheme. By operating at specific working points, the nuclear-spin splitting becomes less sensitive to electrical noise, enabling long coherence times and high-fidelity quantum operations. All elctrical, addressable control of nuclear spins paves the way for scalable silicon-based quantum computing.
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Continuous-wave AC magnetometry up to hundreds of megahertz using nitrogen-vacancy centers under a strong transverse magnetic field
Abstract
Nitrogen-vacancy (NV) centers in diamond are promising quantum sensors for AC magnetic fields. However, conventional dynamical-decoupling-based magnetometry becomes technically demanding at high frequencies because of the requirement for increasingly short and high-power microwave pulses. This paper describes an AC magnetometry technique based on continuous-wave optically detected magnetic resonance (CW-ODMR) measurements, which enables the detection of signals in the hundred-MHz range. By applying a strong static magnetic field transverse to the NV axis, the energy separation between the relevant electron-spin states was tuned and resonantly coupled with the target radiofrequency (RF) magnetic field, thereby forming RF-dressed states. Unlike pulsed dynamical-decoupling schemes, this approach does not require high-power microwave pulse sequences. The key feature of our method is that the detectable frequency can be tuned by controlling the bias magnetic field strength. Using this methodology, we have experimentally achieved the frequency-tunable detection of AC magnetic fields from 14.4-632 MHz. The sensitivity was 0.558 uT/Hz^(0.5) at 14.4 MHz and 24.4 uT/Hz^(0.5) at 632 MHz. We characterized the field-dependent ODMR contrast and linewidth, and found that their degradation at large transverse fields is a important factor limiting the high-frequency sensitivity. These results establish a simple CW-ODMR approach for widely tunable RF magnetic-field sensing without high-power pulsed spin control.
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Remote nonreciprocal magnon magnon entanglement via the Barnett effect with coherent feedback
Abstract
We propose a scheme for generating and controlling remote nonreciprocal magnon--magnon entanglement in a cavity magnonic system with coherent feedback.The two microwave cavities are driven by independent single-mode squeezed vacuum fields, with a rotating YIG sphere in the left cavity and a stationary one in the right cavity. For a fixed rotation direction, reversing the bias magnetic field applied to the rotating sphere changes the sign of the Barnett shift, leading to nonreciprocal magnon--magnon entanglement. By tuning the cavity detuning and feedback phase, entanglement can be generated for one direction of the bias magnetic field while it vanishes for the opposite direction, yielding complete nonreciprocity. Coherent feedback enhances the entanglement at an appropriate reflectivity, whereas stronger feedback can reduce it. The relative squeezing phase provides additional control, and an appropriate choice of unequal squeezing factors improves the entanglement at fixed total input photon occupation. With the squeezed inputs kept fixed, moderate feedback also increases the critical temperature for magnon entanglement.Our results provide a controllable approach to preparing remote nonreciprocal quantum correlations in cavity magnonic systems.
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Quantum Simulation of a Hyperbolically Driven Quantum System with Superconducting Circuits
Abstract
Hyperbolic geometry hosts a plethora of exotic quantum phenomena ranging from holographic duality to novel topological phases. However, investigating these effects experimentally remains challenging due to the Euclidean constraints of natural crystalline materials. While recent synthetic lattices have achieved static realizations, they often lack the dynamical tunability required to explore the full geometric landscape. Here, we overcome these limitations by implementing a quantum simulation of hyperbolic geometry within the parameter space of a superconducting quantum circuit. We construct a Hyperbolically Driven Quantum System (HDQS) by mapping the hyperbolic properties onto the dynamically controllable Hamiltonian parameters. By probing the systems' response under geometric quantum driving, we elucidate how the intrinsic geometry of the parameter space dictates observable physical quantities. Furthermore, we extend the theoretical framework to realize ensemble simulation. This generalization enables us to harness the fast coherent control of superconducting qubits to capture essential geometric characteristics, establishing a versatile platform for exploring quantum dynamics on hyperbolic manifolds.
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Fast entanglement generation via cavity-mediated nematic tensor dynamics
Abstract
Many-body entanglement in atomic ensembles offers the potential for enhanced sensing devices. Entanglement can be generated by interfacing atoms with a cavity. Traditional methods use effective two-level systems isolated from more complex atomic level structures. However, alternative strategies allow entanglement to be generated in atoms confined to a single hyperfine manifold. These strategies enable entanglement in ways fundamentally not available to two-level systems but feature extremely slow dynamics due to requiring strongly off-resonant laser fields. Here, I show that equivalent squeezing dynamics can be achieved much closer to resonance, offering entanglement generation over a hundred times faster than typical experiments. Furthermore, the Hamiltonian can be used to speed up the creation of maximally entangled states via adiabatic passage.
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Design-Time Conformance Checking for Pulse-Level Quantum Control
Abstract
A pulse-level quantum control program is written against a device whose limits are recorded, if at all, in vendor documentation and source code. A program that exceeds them can be refused at compile time. It can also be accepted and silently altered, or compile and then fail at the board. In the last two cases the experiment runs, and the data does not correspond to the program that was written. We present qconform, a checker that decides whether a pulse program is realizable on a device, given a versioned capability descriptor for that device. Every constraint in a descriptor cites the toolchain observation that established it. The checker is design-time, offline, and deterministic, and it uses no floating point. It reports a verdict, the rules it applied, and a coverage manifest that names what it did not check. We evaluate qconform by differential testing against the QICK and Qblox toolchains, on three QICK board configurations and one Qblox cluster. Over 1263 program runs of 969 distinct programs, the checker accepted no program that a toolchain refuses. On both vendors, a descriptor pinned to one toolchain release accepts programs that older releases refuse. The evaluation also found ten defects in the checker and its descriptors, all fixed.
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Geodesic-based optimal control for leakage suppression in superconducting qubits
Abstract
Superconducting qubits are often based on the first two energy levels of a physical anharmonic LC oscillator. Since the anharmonicity of such systems is usually much lower than the involved energy gaps, population can easily leak to higher energy states. This is what characterizes leakage errors, and it can have multiple sources: from coherent error induced by the control platform to incoherent thermal dissipation. In this work, we adapt an optimal control method based on sub-Riemannian geodesic search in the unitary group for a system consisting of two superconducting qubits with leakage levels. We use the $R_x(π/2)$ rotation for single-qubit operation analysis, and the $i$SWAP operation for two-qubit analysis. For the former, we find considerable performance improvement in average gate fidelity as well as in the reduction of leakage errors when comparing the obtained optimal pulses with Gaussian and DRAG pulses, especially for short duration pulses. For the $i$SWAP gate, although leakage error remains roughly the same, we manage to obtain considerably higher fidelities with the cost of requiring a slightly longer time evolution.
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Inertial Counterdiabatic Driving
Abstract
We introduce an inertial counterdiabatic (CD) protocol that reformulates shortcut-to-adiabaticity design as a moving-frame diagonalization problem. The method employs the Magnus expansion to construct a variational propagator generated by an accessible CD ansatz. In the new rotating frame, the controls are optimized to suppress the off-diagonal Hamiltonian terms, and the CD terms are defined to counteract the corresponding inertial contribution. The propagator generated with the Magnus expansion naturally exploits additional control directions generated through its nested commutator, while the sequential design of the propagator introduces temporal nonlocality into the optimization. We benchmark the method on a two-qubit system and on the one-dimensional quantum Ising chain, where it consistently outperforms variational CD protocols based on action minimization. The largest improvements are observed near gap-closing regions, demonstrating the advantage of combining temporal and algebraic nonlocality for suppressing diabatic excitations.
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Protecting bosonic codes from ancilla-induced errors with continuous-variable flags
Abstract
Bosonic quantum error correction represents a route towards significant hardware overhead reduction for fault-tolerant quantum computation. However, controlling quantum harmonic oscillators that encode the quantum information comes with its own challenges. In many platforms such as superconducting circuits and trapped ions, the bosonic degree of freedom is controlled by an ancillary qubit whose decay during a qubit-oscillator gate propagates to the oscillator as a continuous error. Such errors generally lie beyond the scope of errors that the bosonic code is capable of correcting. We introduce the continuous-variable flag: an auxiliary oscillator coupled to the ancilla whose phase-space position encodes the continuous error corrupting the storage mode. After the gate, a heterodyne measurement of the flag estimates this continuous-variable error and a subsequent feedback control undoes it up to a bosonic code stabilizer. The scheme requires no new ingredients, as the flag is driven by the same dispersive coupling, displacements and rotations that implement the gates it is supposed to protect. We construct sequences protecting conditional rotations to all orders in ancilla decay with one flag, and conditional displacements to first order with one flag and to all orders with two. Simulations with realistic circuit-QED parameters predict more than three orders of magnitude fewer logical errors for the parity measurement of a four-component cat code, and a finite-energy GKP logical lifetime near its noiseless-ancilla bound. By discretizing continuous-variable errors, the flags introduced in this work are a useful tool for any hybrid oscillator-qubit processor, and open the route towards fault-tolerant simulation and computation with bosonic modes.
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Out-of-control Hamiltonian Learning
Abstract
Learning the Hamiltonian of a many-body system from its dynamics is a central task in quantum science, yet the algorithms with the strongest provable guarantees assume some level of quantum control--fast, arbitrary single-qubit gates interleaved with time evolution, and measurements in arbitrary bases--that is beyond the capabilities of near-term analog quantum simulators. Motivated by analog atom- and ion-based platforms, we study Hamiltonian learning under minimal access models. Uniform state preparation and measurements: We first consider the setting where in every experiment, one can rotate each qubit to the same state, perform short-time evolution, and measure every qubit in the same basis. Surprisingly, we show that for generic 2-local Hamiltonians on any interaction graph, all of the parameters can be reconstructed from such experiments. Computational basis state preparation and measurements: We then consider a similarly constrained setting, but where state preparation and measurement are restricted to the computational basis. For nearest-neighbor Hamiltonians with only Pauli $X/Z$ interactions, a class which captures contemporary Rydberg atom platforms, we show that over 1D and 2D rectangular lattices, all of the parameters can be reconstructed from such experiments up to unavoidable gauges. Our protocols introduce new techniques for solving structured polynomial systems over an extensive number of parameters. Taken together, our results suggest that one can learn a great deal from the dynamics of quantum many-body systems even under the most stringent experimental constraints.
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Measurement-free Preparation of Surface-Code States with Digital-Analog Counterdiabatic Drivings
Abstract
Preparing stabilizer-code states with shallow circuits is an important primitive for near-term quantum error correction in superconducting circuits, where logical-state initialization requires four-body stabilizer correlations from native one- and two-body controls. We introduce a digital-analog method for the preparation of surface-code ground-state manifolds. The method exploits a structural property of the adiabatic gauge potential, mapping stabilizer-local counterdiabatic terms to digital-analog blocks on the superconducting layout using fixed-angle two-qubit XY gates, single-qubit rotations, and analog exchange-interaction evolutions. The dressed blocks generate higher-order operators used as the variational ansatz to determine the counterdiabatic terms within the Sels-Polkovnikov adiabatic-gauge-potential framework. We benchmark checkerboard plaquette-stabilizer grids up to 4 x 4; the square-grid instances correspond to rotated surface codes, while the rectangular cases probe the scaling of the method. For all grids, the proposed method generates the dominant four-body counterdiabatic basis and, at short evolution times, substantially improves ground-state preparation compared with bare adiabatic evolution. We further generalize the construction to n x m stabilizer lattices and show that digital-analog synthesis can reduce the entangling depth by an order of magnitude. Together, these results establish a direct connection between stabilizer geometry, the structure of the counterdiabatic gauge potential, and digital-analog control for measurement-free preparation of stabilizer-code states on near-term superconducting architectures.
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Suppressing Frequency Collisions in a Quantum Processor
Abstract
Frequency crowding, the close spacing of qubit transitions, limits superconducting quantum processors through crosstalk, leakage, and spectator dependent errors. We introduce a Hamiltonian based framework that maps two- and three-body collision mechanisms onto a Max-k-Cut problem on qubit frequency allocation. In order to make larger lattices tractable, we introduce a cluster-stitching protocol that decomposes larger lattices into overlapping subgraphs and reconciles their local frequency assignments into globally consistent configurations. We tested our proposed framework across multiple qubit architectures to suppress dominant collision penalties by revealing a hardware residual crosstalk. We benchmark digitized counterdiabatic QAOA (DC-QAOA), standard QAOA, and simulated annealing. Counterdiabatic terms improve QAOA optimization near steep collision penalties, while simulated annealing achieves the lowest costs on the tested instances. These results indicate that our hardware-aware optimization connects microscopic interaction physics to processor-level frequency planning. These results enable a systematic solver for benchmarking of scalable software hardware co design.
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Simultaneous Circuit Tests for Finite Reversible Models of Quantum Control
Abstract
A finite reversible model can approximate individual quantum gates while retaining freedom in its transition tables and preparation contexts. We formulate the simultaneous certification problem in which one stationary controller and one preparation law must reproduce an entire collection of circuit probabilities. For a specified frame catalogue, accuracy graph and calibration constraints, we give an exact shared-table feasibility formulation and distinguish certificates for a fixed table from certificates for the complete model class. A four-frame qubit example exhibits a strict separation between fitting two circuits individually and fitting them jointly. A larger exact benchmark uses 464 frames and a phase symmetry that removes preparation-prior dependence. We independently reconstruct its admissible graph and certify a sharp repeated-circuit horizon: one controller stays within probability error 1/3 through 192 blocks, whereas every allowed controller violates that threshold by block 193. A separate controller reproduces all 8,190 nonempty Hadamard-phase words of length at most twelve within the same tolerance. We also derive a finite-window spectral obstruction and finite-shot confidence tests, illustrated by a reproducible sampling experiment. The conclusions concern the stated finite reversible model classes; they do not establish a universal memory bound or a discrepancy for physical quantum hardware.
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JAQSI: Just Another Quantum Simulator
Abstract
Classical simulation supports the development and validation of quantum algorithms through full-state inspection, controlled noise models and backpropagation, albeit for small quantum systems. Existing frameworks offer gate-level execution, differentiable pulse-level dynamics or optimised hardware execution. Just another quantum simulator (JAQSI) combines gate- and pulse-level simulation in one differentiable circuit model built upon JAX. Circuits are represented as pure functions of numerical inputs which support vectorised batches and JIT compilation. Within a single circuit, matrix-defined operations, gates synthesised from Hamiltonian time evolution and noise channels can be composed freely. For a fast simulation, gate and channel fusion reduces passes over the state, while adjoint differentiation computes expectation-value gradients with a constant number of statevectors. At pulse level, JAQSI reduces evolution under single-term Hamiltonians to a scalar pulse-area integral and reuses cached execution plans and compiled solvers. In a benchmark we compare JAQSI with PennyLane, Qiskit, Qibo, Qulacs, QuTiP and dynamiqs. At gate level, we observe performance either on par or an order of magnitude faster across statevector, density, noise and gradient simulation than the compared simulators up to 12 qubits. Beyond 18 qubits, JAQSI is on par with PennyLane Lightning in both statevector and gradient simulation. In the statevector and noisy density-matrix pulse benchmarks, it is at least 5 times faster than the other simulators, even with its closed-form solve disabled. Disabling the latter increases its runtime by at most a factor of 1.5. We provide JAQSI as open-source software on GitHub and PyPI.
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The QICK Box: A Modular RF Front-End System for Quantum Control and Readout
Abstract
The QICK (Quantum Instrumentation Control Kit), first introduced in 2022, is a standalone open source control system for quantum information science. Since then, QICK has been migrated to new hardware platforms, expanded its functionality for applications with different types of qubits (superconducting, atomic, ion-trapped, and spin defects), as well as quantum sensors, and quantum networks. QICK is a highly optimized control kit, with a library of functions that can be used for more than one application. In particular, the software and firmware are customized to minimize latency and maximize control performance and throughput. In this white paper, we describe hardware details and performance of the QICK Box. The QICK Box features up to 16 outputs, up to 8 inputs, and 8 20-bit DC biases. Modular output and input daughtercards give the choice of signal chains optimized for fast DC-coupled signals or RF signals up to 10 GHz. Power levels, step attenuation, and bandpass filtering are controlled by software. We demonstrate the system's performance through single-shot readout measurements of a six-transmon device at the Quantum Underground Instrumentation Experimental Testbed (QUIET) at Fermilab, achieving (91.7 +/- 0.4)% readout fidelity limited by T1 decay during the readout. The single shot readout signal-to-noise ratio (SNR) is 4.4 +/- 0.1 without a quantum amplifier, confirming that the QICK Box is suitable for high-fidelity quantum control and measurement applications. Advances in firmware and software will be described in a separate paper.
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Pulse-resolved post-generation phase control of squeezed light at 93 MHz with a bulk lithium-niobate modulator
Abstract
Time-domain multiplexing of continuous-variable quantum states provides a scalable approach to photonic quantum information processing, in which individual temporal modes can be sequentially manipulated within a common optical path. Here we demonstrate pulse-resolved post-generation phase control of squeezed-vacuum states at a repetition rate of 93 MHz using a low-loss bulk lithium-niobate electro-optic modulator driven by a broadband RF power amplifier. The driving architecture exploits low-cost, commercially available RF components and the impedance mismatch between the RF chain and the capacitive crystal load, rather than relying on dedicated custom high-voltage electronics, to obtain large voltage excursions on the modulator while operating above the piezoelectric-resonance region of lithium niobate. The modulator is driven synchronously with the optical pulse train, enabling the phase of consecutive temporal modes to be individually controlled. An interferometric calibration yields a maximum differential phase excursion of 1.93 rad. We apply the modulator to a 1035 nm squeezed-vacuum field generated by a synchronously pumped optical parametric oscillator and characterize the output using time-resolved balanced homodyne detection. With the local-oscillator phase kept fixed, the phase of the squeezed state is varied from pulse to pulse, and the corresponding phase-dependent quadrature variance is reconstructed. The resulting quadrature scan agrees with an equivalent measurement obtained by varying the local-oscillator phase with a piezoelectric actuator. These results demonstrate post-generation quantum-state phase control at the individual-pulse level and provide an electro-optic building block for programmable manipulation of time-multiplexed quantum states in recirculating optical architectures.
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Investigating entanglement dynamics with dynamical decoupling together with initial qubit-reservoir correlations
Abstract
We study the exact entanglement dynamics of two qubits coupled to a common bosonic reservoir through a pure dephasing interaction. We ask how this dynamics changes when the qubits and the reservoir already share correlations before the qubit state is prepared. In that case the system and reservoir first interact for a long time and settle into a joint equilibrium state. Only afterward is the qubit pair projected onto the desired state by a local measurement. For an Ohmic spectral density we obtain the exact reduced two qubit dynamics. Using the Wootters concurrence we show that initial correlations always speed up entanglement sudden death relative to the factorized case, and that this gap grows quadratically with the coupling strength in the weak-to-moderate coupling regime. Finally we show that a symmetric sequence of periodic π pulses applied to both qubits extends the entanglement lifetime close to a factor of seven over the range of pulse numbers studied.
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Counterdiabatic Quantum Circuits
Abstract
Counterdiabatic driving provides a universal route to fast quantum control, but its standard formulation presupposes a Hamiltonian generator. We develop a Hamiltonian-free theory of the adiabatic gauge potential (AGP) for parameter-dependent unitary operators $U_λ$. Exact and regularized versions of the AGP follow from a Hermitian, banded linear system at a cost comparable to the Lanczos construction in the Hermitian case, requiring neither diagonalization nor a matrix logarithm. We demonstrate rapid convergence of the truncated Krylov approximation for the kicked top and for an integrable brickwork circuit built from unitary $\check{R}$ matrices, a setting in which no local effective Hamiltonian is available. Our results extend shortcuts to adiabaticity, and AGP-based diagnostics of chaos, to Floquet systems and quantum circuits.
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Spiking neural networks for streaming qubit readout
Abstract
Fast and accurate qubit-state assignment is essential for feedback, calibration, and error correction in quantum processors. In superconducting platforms, frequency-multiplexed readout makes this task intrinsically multivariate as measured traces can encode crosstalk, qubit-state relaxation events, and other transient nonidealities that are not fully captured by conventional matched filtering. Here, we introduce spiking neural network (SNN) discriminators for superconducting qubit readout. By processing the measurement window in successive time chunks, the networks exploit temporal structure and update classification scores as data arrive, rather than waiting until the end of the readout window. The spiking networks outperform matched-filter discrimination and approach the accuracy of a full-trace artificial neural network. Beyond reaching the performance of artificial neural networks, the key advantage of SNNs is that they provide a streaming, time-resolved estimate of the qubit state that evolves as the readout signal is acquired. Using quantisation-aware training and hls4ml synthesis, we further demonstrate that each FPGA inference update can be completed before the next readout chunk arrives. These results establish spiking neural networks as a promising route to low-latency, real-time qubit readout on FPGA hardware, with broader implications for time-critical quantum-control and scientific-inference applications.
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State-selective molecular orientation by vibrational Autler-Townes adiabatic passage
Abstract
Control of molecular angular momentum orientation enables state-resolved studies of molecular interactions and provides a basis for quantum information processing. Here we propose all-optical Autler-Townes state-selective adiabatic passage (ASAP) to prepare molecules in a single $|J,M\rangle$ sublevel. An Autler-Townes branch created by a strong coupling field is selectively populated and adiabatically mapped onto the target vibrational state. We resolve detuning-dependent rovibrational Autler-Townes splitting in $^{13}$CO$_2$, establishing the spectroscopic basis for the selective excitation of the target dressed branch. The density-matrix model calibrated by these spectra predicts transfer approaching 90\%. The scheme can exploit millisecond vibrational radiative lifetimes within the electronic ground state and extend to polar and nonpolar molecules with infrared-active vibrational modes.
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The Quantum Sphere: A Physically Realizable Optimization Benchmark with Provable Linear Convergence in White- and Black-Box Settings
Abstract
We revisit an established Quantum Control objective, characterize its exact local metric geometry, and reposition it as a rigorous benchmark for Search and Optimization. The trap-free topology of the landscape, established two decades ago, guarantees unhindered optimal pathways, but global topology alone does not govern convergence speed. Although the so-called Quantum Sphere is defined by the fourth power of the control field, we show that its yield gap admits an exact representation as a nonnegative linear combination of $\sin^2$ terms. From this single identity, we derive a two-sided quadratic sandwich with ratio $4/π^2$ on a certified, worst-case quarter-wave region, proving the optimal peak nondegenerate modulo its affine gauge and well-conditioned. For white-box optimization, on a halved (eighth-wave) region, the objective satisfies a Polyak-Łojasiewicz inequality with an explicit constant, granting Gradient Descent a linear rate of $1 - 16/(π^4κ_r)$, where $κ_r$ is the condition number of the relevant Hessian block. For black-box optimization, we prove that the elitist single-parent Evolution Strategy converges linearly, almost surely and in expected hitting time, from a certified sublevel set, despite the landscape's continuous gauge symmetry and its lattice of periodic optima; the certified level is explicit whenever the landscape is trap-free, and near the optimum the strategy provably sees only the quadratic tangent of the peak. Systematic numerical simulations corroborate the theory. Finally, we show that additive input (actuator) noise reweights each term of the representation by a Debye-Waller factor without disrupting the landscape's structure, and outline open challenges: output (signal) noise, far-field plateau escape, angular-synchronization certificates, and another physically scalable benchmark (SHG with Glass).
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Distinguishing Coherent Crosstalk from Calibration Drift via Pauli-Transfer Signatures and Quantum Edge Detection
Abstract
Multi-tenant quantum processors expose a pulse-level attack surface in which coherent crosstalk can mimic benign calibration drift at matched average gate infidelity. We present a structural verification and detection framework based on the residual Pauli transfer matrix (PTM). We prove that products of local unital, trace-preserving channels cannot mix weight-1 and weight-2 Pauli operators, even under coherent drift of arbitrary strength or axis. Building on established PTM-to-Hamiltonian relations, we prove that, for any specified qubit pair in an arbitrarily large system, the first-order map from its nine interaction coefficients to the antisymmetric cross-weight feature is an isometry up to scale. Thus, every interaction direction is locally observable near the identity. We also exhibit cancellation of this feature under large local rotations and prove that the full cross-weight norm is invariant under local unitary composition, providing a structural countermeasure. For calibrated small local rotations, shared randomized-Pauli measurements support periodic verification using the evaluated antisymmetric detector. In simulation, $16{,}384$ randomized settings yield a detection threshold of $λ_{\min}\approx0.13$ at a $5\%$ calibrated false-positive target, with approximately $M^{-1/2}$ scaling in the number of settings $M$. Further experiments characterize detection under relaxation, depolarization, native ZZ fluctuations, and time-dependent pulse dynamics. Finally, an FRQI encoding with Pauli-graph quantum Hadamard edge detection reproduces the classical structural edge score to numerical precision.