When a high-energy particle, such as a $\gamma$ ray or muon, impacts the substrate of a superconducting qubit chip, large numbers of electron-hole pairs and phonons are created. The ensuing dynamics of the electrons and holes changes the local offset-charge environment for qubits near the impact site. The phonons that are produced have energy above the superconducting gap in the films that compose the qubits, leading to quasiparticle excitations above the superconducting ground state when the phonons impinge on the qubit electrodes. An elevated density of quasiparticles degrades qubit coherence, leading to errors in qubit arrays. Because these pair-breaking phonons spread throughout much of the chip, the errors can be correlated across a large portion of the array, posing a significant challenge for quantum error correction. In order to study the dynamics of $\gamma$-ray impacts on superconducting qubit arrays, we use a $\gamma$-ray source outside the dilution refrigerator to controllably irradiate our devices. By using charge-sensitive transmon qubits, we can measure both the offset-charge shifts and quasiparticle poisoning due to the $\gamma$ irradiation at different doses. We study correlations between offset-charge shifts and quasiparticle poisoning for different qubits in the array and compare these with numerical modeling of charge and phonon dynamics following a $\gamma$-ray impact. We thus characterize the poisoning footprint of these impacts and quantify the performance of structures for mitigating phonon-mediated quasiparticle poisoning.

Kerr-cat qubits are bosonic qubits offering autonomous bit-flip protection, traditionally studied using driven superconducting nonlinear asymmetric inductive element (SNAIL) oscillators. Here, we theoretically explore an alternative circuit for Kerr-cat qubits based on symmetrically threaded superconducting quantum interference devices (SQUIDs). The symmetrically threaded SQUID (STS) architecture employs a simplified flux-pumped design that suppresses two-photon dissipation, a dominant loss mechanism in high-Kerr regimes, by engineering the drive Hamiltonian’s flux operator to generate only even-order harmonics. By fulfilling two critical criteria for practical Kerr-cat qubit operation, the STS emerges as an ideal platform: (1) a static Hamiltonian with diluted Kerr nonlinearity (achieved via the STS’s middle branch) and (2) a drive Hamiltonian restricted to even harmonics, which ensures robust two-photon driving with reduced dissipation. For weak Kerr nonlinearity, we find that the coherent state lifetime ($T_{\alpha }$) is similar between STS and SNAIL circuits. However, STS Kerr-cat qubits exhibit enhanced resistance to higher-order photon dissipation, enabling significantly extended $T_{\alpha }$ even with stronger Kerr nonlinearities (approximately $10$ MHz). In contrast to SNAIL, STS Kerr-cat qubits display a $T_{\alpha }$ dip under weak two-photon driving for a high Kerr coefficient. We demonstrate that this dip can be suppressed by applying drive-dependent detuning, enabling Kerr-cat qubit operation with only eight Josephson junctions (of energies 80 GHz); fewer junctions suffice for higher junction energies. We further validate the robustness of the STS design by studying the impact of strong flux driving and asymmetric Josephson junctions on $T_{\alpha }$. With the proposed design and considering a cat size of ten photons, we predict $T_{\alpha }$ of the order of tens of milliseconds, even in the presence of multiphoton heating and dephasing effects. The robustness of the STS Kerr-cat qubit makes it a promising component for fault-tolerant quantum processors.

Electronic structure calculations of molecular systems are among the most promising applications for fault-tolerant quantum computing (FTQC) in quantum chemistry and drug design. However, while recent algorithmic advancements such as qubitization and tensor hypercontraction (THC) have significantly reduced the complexity of such calculations, they do not yet achieve computational runtimes short enough to be practical for industrially relevant use cases. In this work, we combine several advances to electronic structure calculation for molecular systems, resulting in a 2-orders-of-magnitude speedup of estimated runtimes over prior-art algorithms run on comparable quantum devices. One of these advances is a novel framework for block-invariant symmetry-shifted tensor hypercontraction, with which we achieve the tightest Hamiltonian factorizations reported to date. We compile our algorithm for an active volume (AV) architecture, a technical layout that has recently been proposed for fusion-based photonic quantum hardware. AV compilation contributes towards a lower runtime of our computation by eliminating overheads stemming from connectivity issues in the underlying surface code. We present a detailed benchmark of our approach, focusing primarily on the computationally challenging benchmark molecule P450. Leveraging a number of hardware trade-offs in interleaving-based photonic FTQC, we estimate runtimes for the electronic structure calculation of P450 as a function of the device footprint.

In quantum metrology, a major application of quantum technologies, the ultimate precision of estimating an unknown parameter is often stated in terms of the Cramér-Rao bound. Yet, the latter fails to completely characterize the distribution of estimates in the nonasymptotic regime. Optimizing metrology protocols with respect to the Cramér-Rao bound can therefore lead to surprisingly poor finite-sample performance. This can be avoided by quantifying the quality of a metrology protocol by the probability of obtaining an estimate with a given accuracy. Using this intrinsically single-shot quantity naturally accommodates the finite-sample regime. We show that the fundamental limits of this figure of merit can be quantified through a multihypothesis testing problem between quantum states. Building on this connection, we derive an analogue of the Cramér-Rao bound that contains explicit corrections relevant to the finite-sample regime. We apply the finite-sample metrology framework to the example task of phase estimation with an ensemble of spin-1/2 particles, giving unambiguous evidence that large quantum Fisher information does not guarantee that a metrology protocol has a good finite-sample performance. Overall, analyzing the probability of success allows the reliable study of quantum metrology in the finite-sample regime and opens up a plethora of new avenues for research at the interface of quantum information theory and quantum metrology.

We present and experimentally implement a real-time protocol for calibrating the frequency of a resonantly driven qubit, achieving exponential scaling in calibration precision with the number of measurements, up to the limit imposed by decoherence. The real-time processing capabilities of a classical controller dynamically generate adaptive probing sequences for qubit-frequency estimation. Each probing evolution time and drive frequency are calculated to divide the prior probability distribution into two branches, following a locally optimal strategy that mimics a conventional binary search. The scheme does not require repeated measurements at the same setting, as it accounts for state preparation and measurement errors. Its use of a parametrized probability distribution favors numerical accuracy and computational speed. We show the efficacy of the algorithm by stabilizing a flux-tunable transmon qubit, leading to improved coherence and gate fidelity. As benchmarked by gate-set tomography, the field-programmable gate array (FPGA) powered control electronics partially mitigates non-Markovian noise, which is detrimental to quantum error correction. The mitigation is achieved by dynamically updating and feeding forward the qubit frequency. Our protocol highlights the importance of feedback in improving the calibration and stability of qubits subject to drift and can be readily applied to other qubit platforms.

Quantum computers must achieve large-scale fault-tolerant operation to deliver on their promise of transformational processing power. This will require thousands or millions of high-fidelity quantum gates and similar numbers of qubits. Demonstrations using neutral-atom qubits trapped and manipulated by lasers have shown that this modality can provide high two-qubit gate (cz) fidelities and scalable operation. However, the gates in these demonstrations are driven by lasers that do not resolve individual qubits, with universal computation enabled by physical midcircuit shuttling of the qubits. This relatively slow operation may greatly extend run times for useful large-scale computation. Here, we demonstrate a universal neutral-atom quantum computer with gate rates limited by optical switching times, rather than shuttling, by individually addressing tightly focused laser beams at an array of single atoms. We achieve cz fidelity of 99.35(4)% and local single-qubit $R_Z$ gate fidelity of 99.902(8)%  in both cases accounting for leakage out of the computational basis. Moreover, we demonstrate nondestructive readout of alkali-atom qubits with 0.9(3)% loss, which boosts operational speed. This technique also enables us to measure a state-of-the-art cz fidelity of 99.73(3)% when excluding atom-loss events, which may be mitigated through erasure conversion. Our results represent a critical step toward large-scale fault-tolerant neutral-atom quantum computers that can execute computations on practical timescales.

Unitary $k$-designs are distributions of unitary gates that match the Haar distribution up to its $k\mathrm{th}$ statistical moment. They are a crucial resource for randomized quantum protocols. However, their implementation on encoded logical qubits is nontrivial due to the need for magic gates, which can require a large resource overhead. In this work, we propose an efficient approach to generate unitary designs for encoded qubits in surface codes by applying local unitary rotations (“coherent errors”) on the physical qubits followed by syndrome measurement and error correction. We prove that, under some conditions on the coherent errors (notably including all single-qubit unitaries) and on the error-correcting code, this process induces a unitary transformation of the logical subspace. We numerically show that the ensemble of logical unitaries (indexed by the random syndrome outcomes) converges to a unitary design in the thermodynamic limit, provided that the density or strength of coherent errors is above a finite threshold. This “unitary design” phase transition coincides with the code’s coherent error threshold under optimal decoding. Furthermore, we propose a classical algorithm to simulate the protocol based on a “staircase” implementation of the surface code encoder and decoder circuits. This enables a mapping to a $(1+1)$-dimensional monitored circuit, where we observe an entanglement phase transition (and thus a classical complexity phase transition of the decoding algorithm) coinciding with the aforementioned unitary design phase transition. Our results provide a practical way to realize unitary designs on encoded qubits, with applications including quantum state tomography and benchmarking in error-correcting codes.

The original proposal of quantum key distribution (QKD) was based on ideal single-photon sources, which, 40 years later, are still challenging to develop. Therefore, the development of decoy-state protocols using weak coherent states (WCS) from lasers set the frontier in terms of secure-key rates and distances. Here, we propose and experimentally demonstrate two simple-to-implement QKD protocols that allow practical far from ideal sub-Poissonian photon sources to outperform state-of-the-art WCS. By engineering the photon statistics of a biexciton-exciton cascade in room-temperature single-photon sources based on giant colloidal quantum dots coupled to nanoantennas, we show that either a truncated decoy-state protocol or a heralded-purification protocol can be employed to achieve a significantly increased performance in terms of the maximal allowed channel loss for secure-key creation, which can exceed even that of ideal WCS by more than 3 dB. We then experimentally emulate a BB84 QKD using such a quantum dot source, verifying the superiority of our protocols over the best possible BB84 WCS performance. These protocols can be utilized efficiently on a host of various quantum emitters having controllable photon statistics with a finite photon-number basis, offering a practical approach to QKD without the hindering requirements on the single-photon purity of the photon source.

Sensing a magnetic field with an atomic magnetometer operated in real time presents significant challenges, primarily due to sensor nonlinearity, the presence of noise, and the need for one-shot estimation. To address these challenges, we propose a comprehensive approach that integrates measurement, estimation, and control strategies. Specifically, this involves implementing a quantum nondemolition measurement based on continuous light probing of the atomic ensemble. The resulting photocurrent is then directed into an extended Kalman filter to produce instantaneous estimates of the system’s dynamical parameters. These estimates, in turn, are utilized by a linear quadratic regulator, whose output is applied back to the system through a feedback loop. This procedure automatically steers the atomic ensemble into a spin-squeezed state, yielding a quantum enhancement in precision. Furthermore, thanks to the feedback proposed, the atoms exhibit entanglement even when the measurement data are discarded. To prove that our approach constitutes the optimal strategy in realistic scenarios, we derive ultimate bounds on the estimation error applicable in the presence of both local and collective decoherence, and show that these are indeed attained. Additionally, we demonstrate that, for large ensembles, the extended Kalman filter not only reliably predicts its own estimation error in real time, but also accurately estimates spin squeezing at short timescales.

We generalize the proof of stability of topological order, due to Bravyi, Hastings, and Michalakis, to stabilizer Hamiltonians corresponding to low-density parity-check (LDPC) codes without the restriction of geometric locality in Euclidean space. We consider Hamiltonians $H_0$ defined by $\text{⟦}N,K,d\text{⟧}$ LDPC codes, which obey certain topological quantum order conditions: (i) code distance $d\ge c\log (N)$, implying local indistinguishability of ground states, and (ii) a mild condition on local and global compatibility of ground states—these include good quantum LDPC codes and the toric code on a hyperbolic lattice, among others. We consider stability under weak perturbations that are quasilocal on the interaction graph defined by $H_0$ and that can be represented as sums of bounded-norm terms. As long as the local perturbation strength is smaller than a finite constant, we show that the perturbed Hamiltonian has well-defined spectral bands originating from the $O(1)$ smallest eigenvalues of $H_0$. The band originating from the smallest eigenvalue has $2^K$ states, is separated from the rest of the spectrum by a finite energy gap, and has exponentially narrow bandwidth $\delta =CN{e}^{-\mathrm{\Theta }(d)}$, which is tighter than the best-known bounds even in the Euclidean case. We also obtain that the new ground-state subspace is related to the initial-code subspace by a quasilocal unitary, allowing one to relate their physical properties. Our proof uses an iterative procedure that performs successive rotations to eliminate non-frustration-free terms in the Hamiltonian. Our results extend to quantum Hamiltonians built from classical LDPC codes, which give rise to stable symmetry-breaking phases. These results show that LDPC codes very generally define stable gapped quantum phases, even in the non-Euclidean setting, initiating a systematic study of such phases of matter.

Phases of matter with robust ground-state degeneracy, such as the quantum toric code, are known to be capable of robust quantum information storage. Here, we address the converse question: given a quantum error-correcting code, when does it define a stable gapped quantum phase of matter, whose ground-state degeneracy is robust against perturbations in the thermodynamic limit? We prove that a low-density parity-check (LDPC) code defines such a phase, robust against all few-body perturbations, if its code distance grows at least logarithmically in the number of degrees of freedom, and it exhibits “check soundness.” Many constant-rate quantum LDPC expander codes have such properties, and define stable phases of matter with a constant zero-temperature entropy density, violating the third law of thermodynamics. Our results also show that quantum toric-code phases are robust to spatially nonlocal few-body perturbations. Similarly, phases of matter defined by classical codes are stable against symmetric perturbations. In the classical setting, we present improved locality bounds on the quasiadiabatic evolution operator between two nearby states in the same code phase.

We present a novel quantum Monte Carlo method for evaluating the $\alpha$-stabilizer Rényi entropy (SRE) for any integer $\alpha \ge 2$. By interpreting the $\alpha$-SRE as partition-function ratios, we eliminate the sign problem in the imaginary-time path integral by sampling reduced Pauli strings within a reduced configuration space, which enables efficient classical computations of the $\alpha$-SRE and its derivatives to explore magic in previously inaccessible two- or higher-dimensional systems. We first isolate the free-energy part in $2$-SRE, which is a trivial term. Notably, at quantum critical points in one-dimensional or two-dimensional transverse-field Ising (TFI) models, we reveal nontrivial singularities associated with the characteristic function contribution, directly tied to magic. Their interplay leads to complicated behaviors of $2$-SRE, avoiding extrema at critical points generally. In contrast, analyzing the volume-law correction to SRE reveals a discontinuity tied to criticalities, suggesting that it is more informative than the full-state magic. For conformal critical points, we claim that it could reflect nonlocal magic residing in correlations. Finally, we verify that $2$-SRE fails to characterize magic in mixed states (e.g., Gibbs states), yielding nonphysical results. This work provides a powerful tool for exploring the roles of magic in large-scale many-body systems and reveals the intrinsic relation between magic and many-body physics.

Rapid progress in quantum technology has transformed quantum computing and quantum information science from theoretical possibilities into tangible engineering challenges. Breakthroughs in quantum algorithms, quantum simulations, and quantum error correction are bringing useful quantum computation closer to fruition. These remarkable achievements have been facilitated by advances in quantum characterization, verification, and validation (QCVV). QCVV methods and protocols enable scientists and engineers to scrutinize, understand, and enhance the performance of quantum information-processing devices. In this tutorial, we review the fundamental principles underpinning QCVV, and introduce a diverse array of QCVV tools used by quantum researchers. We define and explain QCVV’s core models and concepts—quantum states, measurements, and processes—and illustrate how these building blocks are leveraged to examine a target system or operation. We survey and introduce protocols ranging from simple qubit characterization to advanced benchmarking methods. Along the way, we provide illustrated examples and detailed descriptions of the protocols, highlight the advantages and disadvantages of each, and discuss their potential scalability to future large-scale quantum computers. This tutorial serves as a guidebook for researchers unfamiliar with the benchmarking and characterization of quantum computers, and also as a detailed reference for experienced practitioners.

The promise of quantum computation is contingent upon physical qubits with both a low gate error rate and broad scalability. Silicon-based spins are a leading qubit platform but demonstrations to date have not utilized fabrication processes capable of extending arrays in two dimensions while maintaining complete control of individual spins. Here, we implement an interconnect process, common in semiconductor manufacturing, with multiple back-end-of-line layers, to show an extendable two-dimensional array of spins with fully controllable nearest-neighbor exchange interactions. In a device using three interconnect layers, we encode exchange-only qubits and achieve average single-qubit gate fidelities consistent with single-layer devices, including fidelities greater than 99.9%, as measured by blind randomized benchmarking. Moreover, with spin connectivity in two dimensions, we show that both linear and right-angle exchange-only qubits with high performance can be formed, enabling qubit array reconfigurability in the presence of defects. This extendable device platform demonstrates that industrial manufacturing techniques can be leveraged for scalable spin qubit technologies.

Direct multiqubit gates are becoming critical to facilitate quantum computations in near-term devices by reducing the gate counts and circuit depth. Here, we demonstrate that fast and high-fidelity three-qubit gates can be realized in a single step by leveraging small anisotropic and chiral three-qubit interactions. These ingredients naturally arise in state-of-the-art spin-based quantum hardware through a combination of spin-orbit interactions and orbital magnetic fields. These interactions resolve the key synchronization issues inherent in protocols relying solely on two-qubit couplings, which significantly limit gate fidelity. We confirm with numerical simulations that our single-step three-qubit gate can outperform existing protocols, potentially achieving infidelity $\le {10}^{-4}$ in 80–100 ns under current experimental conditions. To further benchmark its performance, we also propose an alternative composite three-qubit gate sequence based on anisotropic two-qubit interactions with built-in echo sequence and show that the single-step protocol can outperform it, making it highly suitable for near-term quantum processors.

Product formulas are a popular class of digital quantum simulation algorithms due to their conceptual simplicity, low overhead, and performance, which often exceeds theoretical expectations. Recently, Richardson extrapolation and polynomial interpolation have been proposed to mitigate the Trotter error incurred by the use of these formulas. This work provides a rigorous, general analysis of these techniques for computing time-evolved observables, simplifying the interpolation algorithm in the process, and shows that extrapolation generically improves the performance of product formulas for this task. We demonstrate that, to achieve error $ϵ$ in a simulation of time $T$ using a $p\mathrm{th}$-order product formula with extrapolation, circuit depths of $O(T^{1+1/p}\mathrm{polylog}(1/ϵ))$ are sufficient—an exponential improvement in the precision over product formulas alone. Furthermore, we prove that these algorithms achieve commutator scaling, and improve the $T$ complexity for the interpolation algorithm. By relaxing the requirement of performing exact Chebyshev interpolation, our simplified algorithm eliminates the need for fractional implementations of Trotter steps, reducing computational overhead. Finally, we show these techniques can be combined with the classical shadows method to estimate many time-evolved local observables. Taken together, our findings provide the strongest evidence yet for the utility of Trotter error-mitigation techniques in algorithmic applications.

The birth, life, and death of Maxwell’s demon provoked a profound discussion about the interplay between thermodynamics, computation, and information. Even after its resolution, the demon continues to inspire a multidisciplinary field. This tutorial offers a comprehensive overview of Maxwell’s demon and its enduring influence, bridging classical concepts with modern insights in thermodynamics, information theory, and quantum mechanics.

Quantum simulators have the potential to solve quantum many-body problems that are beyond the reach of classical computers, especially when they feature long-range entanglement. To fulfill their prospects, quantum simulators must be fully controllable, allowing for precise tuning of the microscopic physical parameters that define their implementation. We consider Rydberg-atom arrays, a promising platform for quantum simulations. Experimental control of such arrays is limited by the imprecision on the optical-tweezer positions when assembling the array, hence introducing uncertainties in the simulated Hamiltonian. In this work, we introduce a scalable approach to Hamiltonian learning using graph neural networks (GNNs). We employ the density-matrix renormalization group to generate ground-state snapshots of the transverse-field Ising model realized by the array, for many realizations of the Hamiltonian parameters. Correlation functions reconstructed from these snapshots serve as input data to carry out the training. We demonstrate that our GNN model has a remarkable capacity to extrapolate beyond its training domain, regarding both the size and the shape of the system, yielding an accurate determination of the Hamiltonian parameters with a minimal set of measurements. We prove a theorem establishing a bijective correspondence between the correlation functions and the interaction parameters in the Hamiltonian, which provides a theoretical foundation for our learning algorithm. Our work could open the road to feedback control of the positions of the optical tweezers, hence providing a decisive improvement of analog quantum simulators.

Characters of irreducible representations are ubiquitous in group theory. However, computing characters of some groups such as the symmetric group $S_n$ is a challenging problem known to be #P-hard in the worst case. Here we describe a matrix product state (MPS) algorithm for characters of $S_n$. The algorithm computes an MPS encoding all irreducible characters of a given permutation. It relies on a mapping from characters of $S_n$ to quantum spin chains proposed by Crichigno and Prakash. We also provide a simpler derivation of this mapping. We complement this result by presenting a $\mathrm{poly}(n)$ size quantum circuit that prepares the corresponding MPS obtaining an efficient quantum algorithm for certain sampling problems based on characters of $S_n$. To assess classical hardness of these problems, we present a general reduction from strong simulation (computing a given probability) to weak simulation (sampling with a small error). This reduction applies to any sampling problem with a certain granularity structure and may be of independent interest.

We theoretically propose a tunable implementation of symmetry-protected topological phases of matter in a synthetic superlattice, taking advantage of the long coherence time and exquisite spectral resolutions offered by gravity-tilted optical lattice clocks. We describe a protocol similar to Rabi spectroscopy that can be used to probe the distinct topological properties of our system. We then demonstrate how the sensitivity of clocks and interferometers can be protected from unwanted experimental imperfections offered by the underlying topological robustness. The proposed implementation opens a path to exploiting the unique opportunities offered by symmetry-protected topological phases in state-of-the-art quantum sensors.