We present a superconducting qubit which consists of two strongly coupled modes: one for data storage and one for coupling, allowing faster, higher-fidelity entangling gates and readout. The use of a dedicated coupling mode allows nonlinear couplings of several hundred MHz between the data mode and other elements, with minimal linear coupling to the data mode. Including decoherence, simulations show that this architecture enables microwave-only CZ gates with an infidelity of $8.6\times10^{-5}$ in 17 ns and always-on ZZ interaction less than 0.4 kHz. Numerical simulations also show readout with state assignment error of $1\times10^{-4}$ in 27 ns (assuming quantum efficiency $\eta=0.5$), Purcell-limited lifetime of 167 ms without a Purcell filter, and a mechanism to suppress shot-noise dephasing ($1/\Gamma_{\phi}=15.8$ ms). Single-qubit gate infidelities are below $1\times10^{-5}$ including decoherence. These beyond experimental state-of-the-art gate and readout fidelities rely only on capacitive coupling between arm qubits, making the arm qubit a promising scalable building block for fault-tolerant quantum computers. less

The simulation of entangled ground-states of quantum materials remains challenging for classical computational methods in more than one spatial dimension, and is a prime target for quantum computational advantage. To this end, an important goal is to identify efficient quantum state preparation protocols that minimize the physical qubit number and circuit depth resources required to capture higher-dimensional quantum correlations. This work introduces a quantum circuit compression algorithm for Gaussian fermion states based on the multi-scale entanglement renormalization ansatz (MERA), which provides an exponential reduction in the circuit depth required to approximate highly-entangled ground-states relevant for quantum materials simulations. The algorithm, termed two-dimensional Gaussian MERA ($2d$ GMERA), extends MERA techniques to compress higher-dimensional Gaussian states. Through numerical simulations of the Haldane model on a honeycomb lattice, the method is shown to accurately capture area-law entangled states including topologically trivial insulators, Chern insulators, and critical Dirac semimetals. While Gaussian states alone are classically simulable, this approach establishes empirical upper bounds on quantum resources needed to prepare free fermion states that are adiabatically connected to correlated ground states, providing guidance for implementing these protocols on near-term quantum devices and offering a foundation for simulating more complex quantum materials. Finally, we develop a novel fermion-to-qubit encoding scheme, based on an expanding $2d$ topological order, that enables implementing fermionic rotations via qubit Pauli rotations with constant Pauli weight independent of system size. less

In quantum chemistry, self-consistent field (SCF) algorithms define a nonlinear optimization problem, with both continuous and discrete components. In this work, we derive Hartree-Fock-inspired SCF algorithms that can be exactly written as a sequence of Quadratic Unconstrained Spin/Binary Optimization problems (QUSO/QUBO). We reformulate the optimization problem as a series of MaxCut graph problems, which can be efficiently solved using semi-definite programming techniques. This procedure provides performance guarantees at each SCF step, irrespective of the complexity of the optimization landscape. We numerically demonstrate the QUBO-SCF and MaxCut-SCF methods by studying the hydroxide anion OH- and molecular Nitrogen N2. The largest problem addressed in this study involves a system comprised of 220 qubits (equivalently, spin-orbitals). Our results show that QUBO-SCF and MaxCut-SCF suffer much less from internal instabilities compared with conventional SCF calculations. Additionally, we show that the new SCF algorithms can enhance single-reference methods, such as configuration interaction. Finally, we explore how quantum algorithms for optimization can be applied to the QUSO problems arising from the Hartree-Fock method. Four distinct hybrid-quantum classical approaches are introduced: GAS-SCF, QAOA-SCF, QA-SCF and DQI-SCF. less

Design space exploration (DSE) plays an important role in optimising quantum circuit execution by systematically evaluating different configurations of compilation strategies and hardware settings. In this work, we study the impact of layout methods, qubit routing techniques, compiler optimization levels, and hardware-specific properties, including noise characteristics, topological structures, connectivity densities, and device sizes. By traversing these dimensions, we aim to understand how compilation choices interact with hardware features. A central question in our study is whether carefully selected device parameters and mapping strategies, including initial layouts and routing heuristics, can mitigate hardware-induced errors beyond standard error mitigation methods. Our results show that choosing the right software strategies (e.g., layout and routing) and tailoring hardware properties (e.g., reducing noise or leveraging connectivity) significantly enhances the fidelity of quantum circuit executions. We provide performance estimates using metrics such as circuit depth, gate count, and expected fidelity. These findings highlight the value of hardware-software co-design, especially as quantum systems scale and move toward error-corrected computing. Our simulations, though noisy, include quantum error correction (QEC) scenarios, revealing similar sensitivities to layout and connectivity. This suggests that co-design principles will be vital for integrating QEC in future devices. Overall, we offer practical guidance for co-optimizing mapping, routing, and hardware configuration in real-world quantum computing. less

While experimental advancements continue to expand the capabilities to control and probe non-equilibrium quantum matter at an unprecedented level, the numerical simulation of the dynamics of correlated quantum systems remains a pivotal challenge - especially in intermediate spatial dimensions. Neural quantum states are emerging as a new computational tool to investigate the time evolution of many-body quantum systems in previously inaccessible regimes. We review the recent progress in the field with a focus on the different time propagation methods, an overview of the reported applications, and a discussion of the major current challenges. less

We introduce a new framework for quantum channel discrimination in an adversarial setting, where the tester plays against an adversary who accesses the environmental system and possesses internal quantum memory to perform adaptive strategies. We show that in asymmetric hypothesis testing, the optimal type-II error exponent is precisely characterized by the minimum output channel divergence, a new notion of quantum channel divergence in the worst-case scenario. This serves as a direct analog of the quantum Stein's lemma in the adversarial channel discrimination. Notably, the optimal error exponent can be achieved via simple non-adaptive strategies by the adversary, and its value can be efficiently computed despite its regularization. The strong converse property for quantum channel discrimination also holds in general. This adversarial quantum Stein's lemma is proved by new chain rules for measured and sandwiched relative entropies. Moreover, we derive a generalized version of the entropy accumulation theorem between two arbitrary sequences of quantum channels, extending the existing results from entropy to divergence and providing a solution to the dual formulation of the open problem presented in [IEEE FOCS, pp. 844-850 (2022)]. less

We present the bicycle architecture, a modular quantum computing framework based on high-rate, low-overhead quantum LDPC codes identified in prior work. For two specific bivariate bicycle codes with distances 12 and 18, we construct explicit fault-tolerant logical instruction sets and estimate the logical error rate of the instructions under circuit noise. We develop a compilation strategy adapted to the constraints of the bicycle architecture, enabling large-scale universal quantum circuit execution. Integrating these components, we perform end-to-end resource estimates demonstrating that an order of magnitude larger logical circuits can be implemented with a given number of physical qubits on the bicycle architecture than on surface code architectures. We anticipate further improvements through advances in code constructions, circuit designs, and compilation techniques. less

The accurate simulation of dissipative quantum dynamics subject to a non-Markovian environment poses persistent numerical challenges, in particular for structured environments where sharp mode resonances induce long-time system bath correlations. We present a scalable distributed memory implementation of the Mask Assisted Coarse Graining of Influence Coefficients (MACGIC) - Quasi-Adiabatic Propagator Path Integral (-QUAPI) method that exploits the memory resources of multiple compute nodes and mitigates the memory bottleneck of the method via a new pre-merging algorithm while preserving numerical accuracy. The distributed memory implementation spreads the paths over the computing nodes by means of the MPI protocoll and efficient high level path management is achieved via an implementation based on hash maps. The efficiency of the new implementation is demonstrated in large-scale dissipative quantum dynamics simulations that account for the coupling to a structured non-Markovian environment containing a sharp resonance, a setup for which convergence properties are investigated in depth. Broad applicability and the non-perturbative nature of the simulation method is illustrated via the tuning of the mode resonance frequency of the structured environment with respect to the system frequency. The simulations reveal a splitting of resonances due to strong system-environment interaction and the emergence of sidebands due to multi-excitations of the bosonic mode that are not accounted for in perturbative approaches. The simulations demonstrate the versatility of the new MACGIC-QUAPI method in the presence of strong non-Markovian system bath correlations. less

Crosstalk is a key obstacle to scaling up quantum computers. It may arise from persistent qubit-qubit couplings or dynamically during gate operation, with the latter being particularly difficult to detect. Here, we introduce the perfect entangler spectrum as a means to identify dynamic crosstalk leading to undesired entanglement. It leverages the geometric classification of two-qubit gates in terms of perfect entanglers. We exemplify application of the spectroscopy for fixed-frequency transmons and parametrically driven gates: When scanning the frequency of a spectator qubit, peaks in the perfect entangler spectrum signal dynamic crosstalk, and analysis of the peaks reveals the mechanisms causing the crosstalk. We discuss the experimental implementation of the crosstalk spectroscopy which requires two two-qubit gate tomographies. less

We investigate a nonequilibrium donor-acceptor quantum rectifier system coupled to an anharmonic vibrational mode, treating the vibrational dynamics both as a two-level system and as multilevel system. The time-dependent Fischer information is then calculated by deriving a quantum master equation for the reduced system dynamics. We estimate some key rectifier parameters, the donor energy, the acceptor energy, and the vibrational frequency. We report that there is an optimal time for estimating the donor and acceptor energy. However, the anharmonic mode can be estimated better only in the steadystate. The acceptor energy is found to be most precisely estimable, especially under strong coupling and high bias. Donor energy shows limited sensitivity, while vibrational frequency estimation benefits from low temperatures. This work offers a theoretical foundation for enhancing parameter estimation in nanoscale quantum devices, guiding future sensing and metrological applications in quantronic systems. less

Quantum computers are an ideal platform to study the ground state properties of strongly correlated systems due to the limitation of classical computing techniques particularly for systems exhibiting quantum phase transitions. While the error rates of Noisy Intermediate-Scale Quantum (NISQ) computers are still high, simulating strongly correlated systems on such devices and extracting information of possible phases may be within reach. The frustrated transverse-field Ising model (TFIM) is such a system with multiple ordered magnetic phases. In this study, we simulate a two-dimensional frustrated TFIM with next-nearest-neighbor spin-exchange interactions at zero temperature. The competition between the nearest-neighbor ferromagnetic and next-nearest-neighbor antiferromagnetic coupling gives rise to frustration in the system. Moreover, the presence of quantum fluctuations makes the ground-state phase profile even richer. We use the Variational Quantum Eigensolver (VQE) to compute the phases on a square lattice with periodic boundary conditions for a system of 16 sites (qubits). The trained VQE circuits are compared to exact diagonalization, allowing us to extract error measures of VQE. We focus on the ground-state phase transitions of this model, where VQE succeeds in finding the dominant magnetic phases. The optimized VQE circuits are then executed on the Quantinuum H1-1 trapped-ion quantum computer without using any error mitigation techniques. Our experiments show near perfect recovery of the magnetic phases of the frustrated model through ground-state energy, the energy derivative, and the spin correlation functions. Thus, we show that the trapped-ion quantum processor is able to achieve reliable simulations of a strongly correlated system within the limitations of the VQE approach. less