Transmon qubits are ubiquitously used in superconducting quantum information processor architectures. Strong drives are required to realize fast, high-fidelity, gates and measurements, including parametrically activated processes. Here, we show that even off-resonant drives, in regimes routinely used in experiments, can cause strong modifications to the structure of the transmon spectrum rendering a large part of it chaotic. Accounting for the full nonlinear dynamics of the transmon in a Floquet-Markov formalism, we find that these chaotic states, often neglected through the hypothesis that the anharmonicity is weak, strongly impact the lifetime of the transmon’s computational states. In particular, we observe that chaos-assisted quantum phase slips greatly enhance band dispersions. In the presence of a measurement resonator, we find that approaching chaotic behavior correlates with strong transmon-resonator hybridization, and an average resonator response centered on the bare resonator frequency. These results lead to a photon-number threshold characterizing the appearance of chaos-induced quantum demolition effects during strong-drive operations, such as dispersive qubit readout. The phenomena described here are expected to be present in all circuits based on low-impedance Josephson junctions.

Seen from the modern lens of causal inference, Bell’s theorem is nothing other than the proof that a specific classical causal model cannot explain quantum correlations. It is thus natural to move beyond Bell’s paradigmatic scenario and consider different causal structures. For the specific case of three observable variables, it is known that there are three nontrivial causal networks. Two of those are known to give rise to quantum nonclassicality: the instrumental and the triangle scenarios. Here we analyze the third and remaining one, which we name the Evans scenario, akin to the causal structure underlying the entanglement-swapping experiment. We prove a number of results about this elusive scenario and introduce new and efficient computational tools for its analysis that can also be adapted to deal with more general causal structures. We do not solve its main open problem—whether quantum nonclassical correlations can arise from it—but give a significant step in this direction by proving that postquantum correlations, analogous to the paradigmatic Popescu-Rohrlich box, do violate the constraints imposed by a classical description of the Evans causal structure.

Open quantum systems are ubiquitous in the physical sciences, with widespread applications in the areas of chemistry, condensed-matter physics, material science, optics, and many more. Not surprisingly, there is significant interest in their efficient simulation. However, direct classical simulation quickly becomes intractable with coupling to an environment with an effective dimension that grows exponentially. This raises the question: Can quantum computers help model these complex dynamics? A first step in answering this question requires an understanding of the computational complexity of this task. Here, we map the temporal complexity of a process to the spatial complexity of a many-body state using a computational model known as the process-tensor framework. With this, we are able to explore the simulation complexity of an open quantum system as a dynamic sampling problem: a system coupled to an environment can be probed at successive points in time—accessing multitime correlations. The complexity of multitime sampling, which is an important and interesting problem in its own right, contains the complexity of master equations and stochastic maps as a special case. Our results show how the complexity of the underlying quantum stochastic process corresponds to the complexity of the associated family of master equations for the dynamics. We present both analytical and numerical examples where the multitime sampling of an open quantum system is as complex as sampling from a many-body state that is classically hard. This also implies that the corresponding family of master equations is classically hard. Our results pave the way for studying open quantum systems from a complexity-theoretic perspective, highlighting the role quantum computers will play in our understanding of quantum dynamics.

Originally formulated for macroscopic machines, the laws of thermodynamics were recently shown to hold for quantum systems coupled to ideal sources of work (external classical fields) and heat (systems at equilibrium). Ongoing efforts have been focusing on extending the validity of thermodynamic laws to more realistic, nonideal energy sources. Here, we go beyond these extensions and show that energy exchanges between arbitrary quantum systems are structured by the laws of thermodynamics. We first generalize the second law and identify the associated work and heat exchanges. After recovering known results from ideal work and heat sources, we analyze some consequences of hybrid work and heat sources. We illustrate our general laws with microscopic machines realizing thermodynamic tasks in which elementary quantum systems play the role of simultaneous source of heat and work. Our results open perspectives to understand and optimize the energetic performances of realistic quantum devices, at any scale.

The $T$ center, a silicon-native spin-photon interface with telecommunication-band optical transitions and long-lived microwave qubits, offers an appealing new platform for both optical quantum memory and microwave-to-optical telecommunication-band transduction. A wide range of quantum memory and transduction schemes could be implemented $\mathrm{with}T$ center ensembles with sufficient optical depth, with advantages and disadvantages that depend sensitively on the ensemble properties. In this work we characterize $T$ center spin ensembles to inform device design. We perform the first $T$ ensemble optical depth measurement and calculate the improvement in center density or resonant optical enhancement required for efficient optical quantum memory. We further demonstrate a coherent microwave interface by coherent population trapping and Autler-Townes splitting. We then determine the most promising microwave and optical quantum memory protocol for such ensembles. By estimating the memory efficiency both in free space and in the presence of a cavity, we show that efficient optical memory is possible with reasonable optical density forecasts. Finally, we formulate a transduction proposal and discuss the achievable efficiency and fidelity.

We present the reaction-coordinate polaron-transform (RCPT) framework for generating effective-Hamiltonian models to treat nonequilibrium open quantum systems at strong coupling with harmonic environments. Our approach, which is based on two exact transformations of the Hamiltonian followed by its controlled truncation, ends with a new Hamiltonian with a weakened coupling to the environment. This new effective Hamiltonian mirrors the initial one, except that its parameters are dressed by the system-bath couplings. The power and elegance of the RCPT approach lie in its generality and in its mathematical simplicity, allowing for analytical work and thus profound understanding of the impact of strong system-bath coupling effects on open-quantum-system phenomena. Examples interrogated in this work include canonical models for quantum thermalization, charge and energy transport at the nanoscale, and performance bounds of quantum thermodynamical machines such as absorption refrigerators and thermoelectric generators, as well as the equilibrium and nonequilibrium behavior of many-body dissipative spin chains.

Temporal modes (TMs) of photons provide an appealing high-dimensional encoding basis for quantum information. While techniques to generate TM states have been established, high-dimensional decoding of single-photon TMs remains an open challenge. In this work, we experimentally demonstrate demultiplexing of five-dimensional TMs of single photons with an average fidelity of $0.96\pm 0.01$, characterized via measurement tomography. This is achieved with use of a newly developed device, the multi-output quantum pulse gate (MQPG). We demonstrate a proof-of-principle complete decoder based on the MQPG that operates on any basis from a set of six five-dimensional mutually unbiased bases and is therefore suitable as a receiver for high-dimensional quantum key distribution. Furthermore, we confirm the high-quality operation of the MQPG by performing resource-efficient state tomography with an average fidelity of $0.98\pm 0.02$.

Silicon spin qubits stand out due to their very long coherence times, compatibility with industrial fabrication, and prospect to integrate classical control electronics. To achieve a truly scalable architecture, a coherent mid-range link that moves the electrons between qubit registers has been suggested to solve the signal fan-out problem. Here, we present a blueprint of such a link of 10 $\text{μ}\mathrm{m}$ length, called a spin qubit shuttle, which is based on connecting an array of gates into a small number of sets. To control these sets, only a few voltage control lines are needed and the number of these sets and thus the number of required control signals is independent of the length of this link. We discuss two different operation modes for the spin qubit shuttle: a qubit conveyor, i.e., a potential minimum that smoothly moves laterally, and a bucket brigade, in which the electron is transported through a series of tunnel-coupled quantum dots by adiabatic passage. We find the former approach more promising considering a realistic Si/SiGe device, including potential disorder from the charged defects at the ${\text{Si/SiO}}_2$ layer, as well as typical charge noise. Focusing on the qubit transfer fidelity in the conveyor shuttling mode, we discuss in detail motional narrowing, the interplay between orbital and valley excitation and relaxation in the presence of $g$ factors that depend on orbital and valley state of the electron, and effects from spin hotspots. We find that a transfer fidelity of 99.9% is feasible in Si/SiGe at a speed of approximately $10\text{m/s}$, if the average valley splitting and its inhomogeneity stay within realistic bounds. Operation at low global magnetic field approximately equal to $20\mathrm{mT}$ and material engineering towards high valley splitting is favorable for reaching high fidelities of transfer.

We develop a density-matrix renormalization group (DMRG) algorithm for the simulation of quantum circuits. This algorithm can be seen as the extension of the time-dependent DMRG from the usual situation of Hermitian Hamiltonian matrices to quantum circuits defined by unitary matrices. For small circuit depths, the technique is exact and equivalent to other matrix product state–based techniques. For larger depths, it becomes approximate in exchange for an exponential speed up in computational time. Like an actual quantum computer, the quality of the DMRG results is characterized by a finite fidelity. However, unlike a quantum computer, the fidelity depends strongly on the quantum circuit considered. For the most difficult possible circuit for this technique, the so-called “quantum supremacy” benchmark of Google LLC [Arute et al., Nature 574, 505 (2019)], we find that the DMRG algorithm can generate bit strings of the same quality as the seminal Google experiment on a single computing core. For a more structured circuit used for combinatorial optimization (quantum approximate optimization algorithm), we find a drastic improvement of the DMRG results with error rates dropping by a factor of $100$ compared with random quantum circuits. Our results suggest that the current bottleneck of quantum computers is their fidelities rather than the number of qubits.

Logical gates constitute the building blocks of fault-tolerant quantum computation. While quantum error-corrected memories have been extensively studied in the literature, explicit constructions and detailed analyses of thresholds and resource overheads of universal logical gate sets have so far been limited. In this paper, we present a comprehensive framework for universal fault-tolerant logic motivated by the combined need for (i) platform-independent logical gate definitions, (ii) flexible and scalable tools for numerical analysis, and (iii) exploration of novel schemes for universal logic that improve resource overheads. Central to our framework is the description of logical gates holistically in a way that treats space and time on a similar footing. Focusing on instruments based on surface codes, we introduce explicit, but platform-independent representations of topological logic gates—called logical blocks—and generate new, overhead-efficient methods for universal quantum computation. As a specific example, we propose fault-tolerant schemes based on surface codes concatenated with more general low-density parity check (LDPC) codes, suggesting an alternative path toward LDPC-based quantum computation. The logical blocks framework enables a convenient software-based mapping from an abstract description of the logical gate to a precise set of physical instructions for executing both circuit-based and fusion-based quantum computation (FBQC). Using this, we numerically simulate a surface-code-based universal gate set implemented with FBQC, and verify that the threshold for fault-tolerant gates is consistent with the bulk threshold for memory. We find, however, that boundaries, defects, and twists can significantly impact the logical error rate scaling, with periodic boundary conditions potentially halving resource requirements. Motivated by the favorable logical error rate suppression for boundaryless computation, we introduce a novel computational scheme based on the teleportation of twists that may offer further resource reductions.

Quantum fluctuations constitute the primary noise barrier limiting cavity-based axion-dark-matter searches. In an experiment designed to mimic a real axion search, we employ a quantum enhanced sensing technique to detect a synthetic axionlike microwave tone at an unknown frequency weakly coupled to a resonator, demonstrating a factor-of-5.6 acceleration relative to a quantum limited search for the same tone. This speed-up is achieved by dynamically coupling the resonator mode to a second (readout) mode with balanced swapping and two-mode squeezing interactions, which results in both visibility-bandwidth and peak-visibility increase. A small fractional imbalance between the two interaction rates yields further scan-rate enhancement and we demonstrate that an eightfold acceleration can be achieved.

Most experiments with ultracold atoms in optical lattices have contact interactions and therefore operate at high densities of around one atom per site to observe the effect of strong interactions. Strong ranged interactions can be generated via Rydberg dressing, which opens up the path to exploring the physics of few interacting particles. Rather than the unit cells of a crystal, the sites of the optical lattice can now be interpreted as discretized space. This allows the study of completely new types of problems in a familiar architecture. We investigate the possibility of realizing problems akin to those found in quantum chemistry, although with a different scaling law in the interactions. Through numerical simulation, we show that simple pseudoatoms and pseudomolecules could be prepared with high fidelity in state-of-the-art experiments.

An external drive can improve the coherence of a quantum many-body system by averaging out noise sources. It can also be used to realize models that are inaccessible in the static limit, through Floquet Hamiltonian engineering. The full possibilities for combining these tools remain unexplored. We develop the requirements needed for a pulse sequence to decouple a quantum many-body system from an external field without altering the intended dynamics. Demonstrating this technique experimentally in an ion-trap platform, we show that it can provide a large improvement to coherence in real-world applications. Finally, we engineer an approximate quantum simulation of the Haldane-Shastry model, an exactly solvable paradigm for long-range interacting spins. Our results expand and unify the quantum simulation toolbox.

Realization of a room-temperature ultrafast photon-number-resolving quantum nondemolition (QND) measurement would have significant implications for photonic quantum information processing, enabling, for example, deterministic quantum computation in discrete-variable architectures, but the requirement for strong coupling has hampered the development of scalable implementations. In this work, we propose and analyze a nonlinear-optical route to photon-number-resolving QND using quadratic (i.e., ${\chi }^{(2)}$) nonlinear interactions. We show that the coherent pump field driving a frequency-detuned optical parametric amplifier (OPA) experiences displacements conditioned on the number of signal Bogoliubov excitations. A measurement of the pump displacement thus provides a QND measurement of the signal Bogoliubov excitations, projecting the signal mode to a squeezed photon-number state. We then show how our nonlinear OPA dynamics can be utilized to deterministically generate Gottesman-Kitaev-Preskill states with only additional Gaussian resources, offering an all-optical route for fault-tolerant quantum information processing in continuous-variable systems. Finally, we place these QND schemes into a more traditional context by highlighting analogies between the frequency-detuned optical parametric oscillator and multilevel atom-cavity quantum electrodynamics systems by showing how continuous monitoring of the outcoupled pump quadrature induces conditional localization of the intracavity signal mode onto squeezed photon-number states. Our analysis suggests that our proposal may be viable in near-term ${\chi }^{(2)}$ nonlinear nanophotonics, highlighting the rich potential of the OPA as a universal tool for ultrafast non-Gaussian quantum state engineering and quantum computation.

Thermodynamics connects our knowledge of the world to our capability to manipulate and thus to control it. This crucial role of control is exemplified by the third law of thermodynamics, Nernst’s unattainability principle, which states that infinite resources are required to cool a system to absolute zero temperature. But what are these resources and how should they be utilized? And how does this relate to Landauer’s principle that famously connects information and thermodynamics? We answer these questions by providing a framework for identifying the resources that enable the creation of pure quantum states. We show that perfect cooling is possible with Landauer energy cost given infinite time or control complexity. However, such optimal protocols require complex unitaries generated by an external work source. Restricting to unitaries that can be run solely via a heat engine, we derive a novel Carnot-Landauer limit, along with protocols for its saturation. This generalizes Landauer’s principle to a fully thermodynamic setting, leading to a unification with the third law and emphasizes the importance of control in quantum thermodynamics.

Monitored quantum dynamics reveal quantum state trajectories, which exhibit a rich phenomenology of entanglement structures, including a transition from a weakly monitored volume-law-entangled phase to a strongly monitored area-law phase. For one-dimensional hybrid circuits with both random unitary dynamics and interspersed measurements, we combine analytic mappings to an effective statistical mechanics model with extensive numerical simulations on hybrid Clifford circuits to demonstrate that the universal entanglement properties of the volume-law phase can be quantitatively described by a fluctuating entanglement domain wall that is equivalent to a “directed polymer in a random environment” (DPRE). This relationship improves upon a qualitative “mean-field” statistical mechanics of the volume-law-entangled phase [Ruihua Fan, Sagar Vijay, Ashvin Vishwanath, and Yi-Zhuang You, Phys. Rev. B 103, 174309 (2021), Yaodong Li and Matthew P. A. Fisher, Phys. Rev. B 103, 104306 (2021)]. For the Clifford circuit in various geometries, we obtain agreement between the subleading entanglement entropies and error-correcting properties of the volume-law phase (which quantify its stability to projective measurements) with predictions of the DPRE. We further demonstrate that depolarizing noise in the hybrid dynamics near the final circuit time can drive a continuous phase transition to a non-error-correcting volume-law phase that is not immune to the disentangling action of projective measurements. We observe this transition in hybrid Clifford dynamics, and obtain quantitative agreement with critical exponents for a “pinning” phase transition of the DPRE in the presence of an attractive interface.

Emerging communication and cryptography applications call for reliable fast unpredictable random number generators. Quantum random number generation allows for the creation of truly unpredictable numbers due to the inherent randomness available in quantum mechanics. A popular approach is to use the quantum vacuum state to generate random numbers. While convenient, this approach has been generally limited in speed compared to other schemes. Here, through custom codesign of optoelectronic integrated circuits and side-information reduction by digital filtering, we experimentally demonstrate an ultrafast generation rate of 100 Gbit/s, setting a new record for vacuum-based quantum random number generation by one order of magnitude. Furthermore, our experimental demonstrations are well supported by an upgraded device-dependent framework that is secure against both classical and quantum side information and that also properly considers the nonlinearity in the digitization process. This ultrafast secure random number generator in the chip-scale platform holds promise for next-generation communication and cryptography applications.

We propose and demonstrate complete spin state readout of a two-electron system in a double quantum dot probed by an electrometer. The protocol is based on repetitive single-shot measurements using Pauli spin blockade and our ability to tune on fast timescales the detuning and the interdot tunnel coupling between the GHz and sub-Hz regime. A sequence of three distinct manipulations and measurements allows establishing if the spins are in $S$, $T_0$, $T_{+}$, or $T_{-}$ state. This work points at a procedure to reduce the overhead for spin readout, an important challenge for scaling up spin-qubit platforms.

Variational quantum machine learning is an extensively studied application of near-term quantum computers. The success of variational quantum learning models crucially depends on finding a suitable parametrization of the model that encodes an inductive bias relevant to the learning task. However, precious little is known about guiding principles for the construction of suitable parametrizations. In this work, we holistically explore when and how symmetries of the learning problem can be exploited to construct quantum learning models with outcomes invariant under the symmetry of the learning task. Building on tools from representation theory, we show how a standard gateset can be transformed into an equivariant gateset that respects the symmetries of the problem at hand through a process of gate symmetrization. We benchmark the proposed methods on two toy problems that feature a nontrivial symmetry and observe a substantial increase in generalization performance. As our tools can also be applied in a straightforward way to other variational problems with symmetric structure, we show how equivariant gatesets can be used in variational quantum eigensolvers.

We present a quantum circuit optimization technique that takes into account the variability in error rates that is inherent across present-day noisy quantum computing platforms. This method can be run after qubit routing or postcompilation and consists of computing isomorphic subgraphs to input circuits and scoring each using heuristic cost functions derived from system calibration data. Using an independent standard algorithmic test suite, we show that it is possible to recover on average nearly 40% of missing fidelity using better qubit selection via efficient to compute cost functions. We demonstrate additional performance gains by considering qubit placement over multiple quantum processors. The overhead from these tools is minimal with respect to other compilation steps, such as qubit routing, as the number of qubits increases. As such, our method can be used to find qubit mappings for problems at the scale of quantum advantage and beyond.