arXiv subjects

Daniel Lidar

Publications and source records attributed to Daniel Lidar.

At least 19 recordsLinked to original sources

arXiv2026

Proof of the Error Scaling for Universally Robust Dynamical Decoupling Sequences

Universally robust dynamical decoupling (UR$n$) sequences were proposed to compensate pulse imperfections arising from arbitrary experimental parameters while achieving high-order error suppression with only a linear increase in the number of pulses. Although their performance was supported by analytical arguments, numerical simulations, and experiments, a complete mathematical proof of the claimed order of error compensation has been absent. In this work, we present a rigorous proof for UR$n$ DD sequences with even $n$. Using a series expansion of a quantity whose modulus is the fidelity $F$, we derive necessary and sufficient conditions for the cancellation of its coefficients up to, but not including, order $n$. The UR$n$ phase prescription satisfies these conditions, and therefore $1-F=O(\epsilon^n)$. Our results establish the UR$n$ construction on firm analytical grounds and clarify the structure responsible for its high-order robustness.

quant-ph↗

arXiv2026

Compressed Sensing Shadow Tomography

Estimating many local expectation values over time is a central measurement bottleneck in quantum simulation and device characterization. We study the task of reconstructing the Pauli-signal matrix $S_{ij}=\text{Tr}(O_i \rho(t_j))$ for a collection of $M$ low-weight Pauli observables $\{O_i\}_{i=1}^M$ over $N$ timesteps $\{t_j\}_{j=1}^N$, while minimizing the total number of device shots. We propose a Compressed Sensing Shadow Tomography (CSST) protocol that combines two complementary reductions. First, local classical shadows reduce the observable dimension by enabling many Pauli expectation values to be estimated from the same randomized snapshots at a fixed time. Second, compressed sensing reduces the time dimension by exploiting the fact that many expectation-value traces are spectrally sparse or compressible in a unitary (e.g., Fourier) transform basis. Operationally, CSST samples $m\ll N$ timesteps uniformly at random, collects shadows only at those times, and then reconstructs each length-$N$ signal via standard $\ell_1$-based recovery in the unitary transform domain. We provide end-to-end guarantees that explicitly combine shadow estimation error with compressed sensing recovery bounds. For exactly $s$-sparse signals in a unitary transform basis, we show that $m=O \left(s\log^2 s \log N\right)$ random timesteps suffice (with high probability), leading to total-shot savings scaling as $\widetilde{\Theta}(N/s)$ (i.e., up to polylogarithmic factors) relative to collecting shadows at all $N$ timesteps. For approximately sparse signals, the reconstruction error decomposes into a compressibility (tail) term plus a noise term. We present numerical experiments on noisy many-qubit dynamics that support strong Fourier compressibility of Pauli traces and demonstrate substantial shot reductions with accurate reconstruction.

quant-ph↗

arXiv2025

Digital-Analog-Digital Quantum Supremacy

Quantum supremacy has been explored extensively in gate-model settings. Here, we introduce a quantum-supremacy framework for a hybrid digital-analog-digital quantum computing (DADQC) model. We consider a device that applies an initial layer of single-qubit gates, a single transverse-field Ising analog block, and a final single-qubit layer before $Z$-basis readout. The analog block approximates $Z$-diagonal Ising evolution, and we prove that the resulting output distribution is within constant total-variation (TV) distance of an Instantaneous Quantum Polynomial-time (IQP) circuit. Our bounds and constructions are established for fully connected as well as bounded-degree hardware graphs, matching a variety of architectures, including trapped-ion, neutral atom, and superconducting platforms. Assuming anticoncentration (which we prove for all-to-all hardware graphs and conjecture for bounded-degree hardware graphs) and an average-case hardness conjecture for the associated complex-temperature Ising partition functions, standard reductions imply that any efficient classical sampler achieving constant TV error collapses the polynomial hierarchy. Our results imply that quantum-supremacy tests are possible on today's quantum annealers, as well as other devices capable of hybrid digital-analog quantum evolution.

quant-ph↗

arXiv2025

Computational Complexity and Simulability of Non-Hermitian Quantum Dynamics

Non-Hermitian (NH) quantum systems demonstrate striking differences from their Hermitian counterparts, leading to claims of NH advantage in areas ranging from metrology to entanglement generation. We show that in the context of quantum computation, any such NH advantage is unlikely to be scalable as an efficient computational resource: if coherent normalized non-unitary evolution could be realized with only polynomial overhead, then the resulting model could implement postselection, implying implausibly strong complexity-theoretic power under standard assumptions. We define NHBQP(U) as the computational power of poly-size quantum circuits that, in addition to a standard universal unitary gate set, may apply a fixed gate U on $O(1)$ qubits that is not proportional to a unitary, with the state renormalized after each use of U. We prove this model is powerful enough to decide PostBQP. In the standard uniform circuit-family model this characterization is tight: for any fixed such U, NHBQP(U)=PostBQP=PP. PostBQP is believed intractable, so this suggests that any scalable NH computational advantage must come with a cost limiting its efficiency. Additionally, we study locality-preserving purifications of restricted classes of non-unitary systems. Using this framework, we show that unitary gates with postselection can simulate not only evolution under NH Hamiltonians but arbitrary quantum trajectories. Any NH model whose purification lies in a strongly simulable unitary family (e.g., Clifford, matchgate, or low-bond-dimension tensor-network circuits) remains efficiently classically simulable, provided the relevant postselected events occur with probability $\Omega(2^{-\text{poly}(n)})$. Thus adding non-Hermiticity to a universal unitary system makes it infeasibly computationally powerful, while adding it to a strongly simulable system adds no computational power in this setting.

quant-ph↗

arXiv2024

ClassiFIM: An Unsupervised Method To Detect Phase Transitions

Estimation of the Fisher Information Metric (FIM-estimation) is an important task that arises in unsupervised learning of phase transitions, a problem proposed by physicists. This work completes the definition of the task by defining rigorous evaluation metrics distMSE, distMSEPS, and distRE and introduces ClassiFIM, a novel machine learning method designed to solve the FIM-estimation task. Unlike existing methods for unsupervised learning of phase transitions, ClassiFIM directly estimates a well-defined quantity (the FIM), allowing it to be rigorously compared to any present and future other methods that estimate the same. ClassiFIM transforms a dataset for the FIM-estimation task into a dataset for an auxiliary binary classification task and involves selecting and training a model for the latter. We prove that the output of ClassiFIM approaches the exact FIM in the limit of infinite dataset size and under certain regularity conditions. We implement ClassiFIM on multiple datasets, including datasets describing classical and quantum phase transitions, and find that it achieves a good ground truth approximation with modest computational resources. Furthermore, we independently implement two alternative state-of-the-art methods for unsupervised estimation of phase transition locations on the same datasets and find that ClassiFIM predicts such locations at least as well as these other methods. To emphasize the generality of our method, we also propose and generate the MNIST-CNN dataset, which consists of the output of CNNs trained on MNIST for different hyperparameter choices. Using ClassiFIM on this dataset suggests there is a phase transition in the distribution of image-prediction pairs for CNNs trained on MNIST, demonstrating the broad scope of FIM-estimation beyond physics.

cs.LG↗

arXiv2024

Detecting Quantum and Classical Phase Transitions via Unsupervised Machine Learning of the Fisher Information Metric

The detection of quantum and classical phase transitions in the absence of an order parameter is possible using the Fisher information metric (FIM), also known as fidelity susceptibility. Here, we propose and investigate an unsupervised machine learning (ML) task: estimating the FIM given limited samples from a multivariate probability distribution of measurements made throughout the phase diagram. We utilize an unsupervised ML method called ClassiFIM (developed in a companion paper) to solve this task and demonstrate its empirical effectiveness in detecting both quantum and classical phase transitions using a variety of spin and fermionic models, for which we generate several publicly available datasets with accompanying ground-truth FIM. We find that ClassiFIM reliably detects both topological (e.g., XXZ chain) and dynamical (e.g., metal-insulator transition in Hubbard model) quantum phase transitions. We perform a detailed quantitative comparison with prior unsupervised ML methods for detecting quantum phase transitions. We demonstrate that ClassiFIM is competitive with these prior methods in terms of appropriate accuracy metrics while requiring significantly less resource-intensive training data compared to the original formulation of the prior methods. In particular, ClassiFIM only requires classical (single-basis) measurements. As part of our methodology development, we prove several theorems connecting the classical and quantum fidelity susceptibilities through equalities or bounds. We also significantly expand the existence conditions of the fidelity susceptibility, e.g., by relaxing standard differentiability conditions. These results may be of independent interest to the mathematical physics community.

quant-ph↗

arXiv2024

Simulating nonlinear optical processes on a superconducting quantum device

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modeled as wave-wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

physics.plasm-ph↗

arXiv2024

Markovian and non-Markovian master equations versus an exactly solvable model of a qubit in a cavity

Quantum master equations are commonly used to model the dynamics of open quantum systems, but their accuracy is rarely compared with the analytical solution of exactly solvable models. In this work, we perform such a comparison for the damped Jaynes-Cummings model of a qubit in a leaky cavity, for which an analytical solution is available in the one-excitation subspace. We consider the non-Markovian time-convolutionless master equation up to the second (Redfield) and fourth orders as well as three types of Markovian master equations: the coarse-grained, cumulant, and standard rotating-wave approximation (RWA) Lindblad equations. We compare the exact solution to these master equations for three different spectral densities: impulse, Ohmic, and triangular. We demonstrate that the coarse-grained master equation outperforms the standard RWA-based Lindblad master equation for weak coupling or high qubit frequency (relative to the spectral density high-frequency cutoff $\omega_c$), where the Markovian approximation is valid. In the presence of non-Markovian effects characterized by oscillatory, non-decaying behavior, the TCL approximation closely matches the exact solution for short evolution times (in units of $\omega_c^{-1}$) even outside the regime of validity of the Markovian approximations. For long evolution times, all master equations perform poorly, as quantified in terms of the trace-norm distance from the exact solution. The fourth-order time-convolutionless master equation achieves the top performance in all cases. Our results highlight the need for reliable approximation methods to describe open-system quantum dynamics beyond the short-time limit.

quant-ph↗

arXiv2024

Quantum Fourier Transform using Dynamic Circuits

In dynamic quantum circuits, classical information from mid-circuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the $n$-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced from $O(n^2)$ two-qubit gates in an all-to-all connectivity in the standard unitary formulation to $O(n)$ mid-circuit measurements in its dynamic counterpart without any connectivity constraints. Here, we demonstrate the advantage of dynamic quantum circuits for the quantum Fourier transform on IBM's superconducting quantum hardware with certified process fidelities of $>50\%$ on up to $16$ qubits and $>1\%$ on up to $37$ qubits, exceeding previous reports across all quantum computing platforms. These results are enabled by our contribution of an efficient method for certifying the process fidelity, as well as of a dynamical decoupling protocol for error suppression during mid-circuit measurements and feed-forward within a dynamic quantum circuit that we call ``feed-forward-compensated dynamical decoupling" (FC-DD). Our results demonstrate the advantages of leveraging dynamic circuits in optimizing the compilation of quantum algorithms.

quant-ph↗

arXiv2024

Dynamically Generated Decoherence-Free Subspaces and Subsystems on Superconducting Qubits

Decoherence-free subspaces and subsystems (DFS) preserve quantum information by encoding it into symmetry-protected states unaffected by decoherence. An inherent DFS of a given experimental system may not exist; however, through the use of dynamical decoupling (DD), one can induce symmetries that support DFSs. Here, we provide the first experimental demonstration of DD-generated DFS logical qubits. Utilizing IBM Quantum superconducting processors, we investigate two and three-qubit DFS codes comprising up to six and seven noninteracting logical qubits, respectively. Through a combination of DD and error detection, we show that DFS logical qubits can achieve up to a 23% improvement in state preservation fidelity over physical qubits subject to DD alone. This constitutes a beyond-breakeven fidelity improvement for DFS-encoded qubits. Our results showcase the potential utility of DFS codes as a pathway toward enhanced computational accuracy via logical encoding on quantum processors.

quant-ph↗

arXiv2024

Error budget of parametric resonance entangling gate with a tunable coupler

We analyze the experimental error budget of parametric resonance gates in a tunable coupler architecture. We identify and characterize various sources of errors, including incoherent, leakage, amplitude, and phase errors. By varying the two-qubit gate time, we explore the dynamics of these errors and their impact on the gate fidelity. To accurately capture the impact of incoherent errors on gate fidelity, we measure the coherence times of qubits under gate operating conditions. Our findings reveal that the incoherent errors, mainly arising from qubit relaxation and dephasing due to white noise, limit the fidelity of the two-qubit gates. Moreover, we demonstrate that leakage to noncomputational states is the second largest contributor to the two-qubit gates infidelity, as characterized using leakage-randomized benchmarking. The error budgeting methodology we developed here can be effectively applied to other types of gate implementations.

quant-ph↗

arXiv2022

Better-than-classical Grover search via quantum error detection and suppression

Grover's search algorithm is one of the first quantum algorithms to exhibit a provable quantum advantage. It forms the backbone of numerous quantum applications and is widely used in benchmarking efforts. Here, we report better-than-classical success probabilities for a complete Grover search algorithm on the largest scale demonstrated to date, of up to five qubits, using two different IBM superconducting transmon qubit platforms. This is enabled, on the four and five-qubit scale, by error suppression via robust dynamical decoupling pulse sequences, without which we do not observe better-than-classical results. Further improvements arise after the use of measurement error mitigation, but the latter is insufficient by itself for achieving better-than-classical performance. For two qubits, we demonstrate a success probability of 99.5% via the use of the [[4,2,2]] quantum error-detection (QED) code. This constitutes a demonstration of quantum algorithmic breakeven via QED. Along the way, we introduce algorithmic error tomography, a method of independent interest that provides a holistic view of the errors accumulated throughout an entire quantum algorithm, filtered via the errors detected by the QED code used to encode the circuit. We demonstrate that algorithmic error tomography provides a stringent test of an error model based on a combination of amplitude damping, dephasing, and depolarization.

quant-ph↗

arXiv2022

No ((n, k, d < 127)) code can violate the quantum Hamming bound

It is well-known that pure quantum error correcting codes (QECCs) are constrained by a quantum version of the Hamming bound. Whether impure codes also obey such a bound, however, remains a long-standing question with practical implications for the efficacy of QECCs. We employ a combination of previously derived bounds on QECCs to demonstrate that a subset of all codes must obey the quantum Hamming bound. Specifically, we combine an analytical bound due to Rains with a numerical bound due to Li and Xing to show that no ((n,k,d < 127)) code can violate the quantum Hamming bound.

quant-ph↗

arXiv2022

Demonstration of error-suppressed quantum annealing via boundary cancellation

The boundary cancellation theorem for open systems extends the standard quantum adiabatic theorem: assuming the gap of the Liouvillian does not vanish, the distance between a state prepared by a boundary cancelling adiabatic protocol and the steady state of the system shrinks as a power of the number of vanishing time derivatives of the Hamiltonian at the end of the preparation. Here we generalize the boundary cancellation theorem so that it applies also to the case where the Liouvillian gap vanishes, and consider the effect of dynamical freezing of the evolution. We experimentally test the predictions of the boundary cancellation theorem using quantum annealing hardware, and find qualitative agreement with the predicted error suppression despite using annealing schedules that only approximate the required smooth schedules. Performance is further improved by using quantum annealing correction, and we demonstrate that the boundary cancellation protocol is significantly more robust to parameter variations than protocols which employ pausing to enhance the probability of finding the ground state.

quant-ph↗

arXiv2021

Predicting non-Markovian superconducting qubit dynamics from tomographic reconstruction

Non-Markovian noise presents a particularly relevant challenge in understanding and combating decoherence in quantum computers, yet is challenging to capture in terms of simple models. Here we show that a simple phenomenological dynamical model known as the post-Markovian master equation (PMME) accurately captures and predicts non-Markovian noise in a superconducting qubit system. The PMME is constructed using experimentally measured state dynamics of an IBM Quantum Experience cloud-based quantum processor, and the model thus constructed successfully predicts the non-Markovian dynamics observed in later experiments. The model also allows the extraction of information about cross-talk and measures of non-Markovianity. We demonstrate definitively that the PMME model predicts subsequent dynamics of the processor better than the standard Markovian master equation.

quant-ph↗

arXiv2021

Low overhead universality and quantum supremacy using only $Z$-control

We consider a model of quantum computation we call "Varying-$Z$" (V$Z$), defined by applying controllable $Z$-diagonal Hamiltonians in the presence of a uniform and constant external $X$-field, and prove that it is universal, even in 1D. Universality is demonstrated by construction of a universal gate set with $O(1)$ depth overhead. We then use this construction to describe a circuit whose output distribution cannot be classically simulated unless the polynomial hierarchy collapses, with the goal of providing a low-resource method of demonstrating quantum supremacy. The V$Z$ model can achieve quantum supremacy in $O(n)$ depth, equivalent to the random circuit sampling models despite a higher degree of homogeneity: it requires no individually addressed $X$-control.

quant-ph↗

arXiv2020

Fast, Lifetime-Preserving Readout for High-Coherence Quantum Annealers

We demonstrate, for the first time, that a quantum flux parametron (QFP) is capable of acting as both isolator and amplifier in the readout circuit of a capacitively shunted flux qubit (CSFQ). By treating the QFP like a tunable coupler and biasing it such that the coupling is off, we show that $T_1$ of the CSFQ is not impacted by Purcell loss from its low-Q readout resonator ($Q_e = 760$) despite being detuned by only $40$ MHz. When annealed, the QFP amplifies the qubit's persistent current signal such that it generates a flux qubit-state-dependent frequency shift of $85$ MHz in the readout resonator, which is over $9$ times its linewidth. The device is shown to read out a flux qubit in the persistent current basis with fidelities surpassing $98.6\%$ with only $80$ ns integration, and reaches fidelities of $99.6\%$ when integrated for $1$ $\mu$s. This combination of speed and isolation is critical to the readout of high-coherence quantum annealers.

quant-ph↗

arXiv2020

Boundaries of quantum supremacy via random circuit sampling

Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling, that is beyond the practical reach of modern supercomputers. We examine the constraints of the observed quantum runtime advantage in an extrapolation to circuits with a larger number of qubits and gates. Due to the exponential decrease of the experimental fidelity with the number of qubits and gates, we demonstrate for current fidelities a theoretical classical runtime advantage for circuits deeper than a few hundred gates, while quantum runtimes for cross-entropy benchmarking limit the region of a quantum advantage to a few hundred qubits. However, the quantum runtime advantage boundary in circuit width and depth grows exponentially with respect to reduced error rates, and our work highlights the importance of continued progress along this line. Extrapolations of measured error rates suggest that the limiting circuit size for which a computationally feasible quantum runtime advantage in cross-entropy benchmarking can be achieved approximately coincides with expectations for early implementations of the surface code and other quantum error correction methods. Thus the boundaries of quantum supremacy via random circuit sampling may fortuitously coincide with the advent of scalable, error corrected quantum computing in the near term.

quant-ph↗