In this paper, we introduce a new approach to quantum benchmarking inspired by quantum verification, motivating new paradigms in quantum benchmarking. Our proposed benchmark not only serves as a robust indicator of computational capability but also offers scalability, customizability, and universality. By providing formal statements regarding the quality of quantum devices while assuming device consistency

Continuous-variable (CV) codes and their application in quantum communication have attracted increasing attention. In particular, one typical CV codes, cat-codes, has already been experimentally created using trapped atoms in cavities with relatively high fidelities. However, when these codes are used in a repeater protocol, the secret key rate (SKR) that can be extracted between two remote users is

The learner’s ability to generate a hypothesis that closely approximates the target function is crucial in machine learning. Achieving this requires sufficient data; however, unauthorized access by an eavesdropping learner can lead to security risks. Thus, it is important to ensure the performance of the ‘authorized’ learner by limiting the quality of the training data accessible to eavesdroppers.

Weak value amplification is crucial in quantum metrology because it enhances the detection of subtle interactions between quantum entities. However, current weak value quantum metrology techniques are only effective for extremely weak interactions, significantly narrowing its range of potential applications. In this work, we present the ‘metrological weak value (MWV)’, designed for use with quantum

We report on the preparation of a large quantum register of 5612 qubits, with the unprecedented high global fidelity of . This was achieved by applying an improved cooperative quantum information erasure protocol (Buffoni and Campisi 2023 Quantum7 961) to a programmable network of superconducting qubits featuring a high connectivity. At variance with the standard method based on the individual reset

We show how to entangle two cavity-magnon polaritons (CMPs) formed by two strongly coupled microwave cavity and magnon modes. This is realized by introducing vibration phonons, via magnetostriction, into the system that are dispersively coupled to the magnon mode. Stationary entanglement between two CMPs can be achieved when they are respectively resonant with the two sidebands of the drive field scattered

Trapped-ion hardware based on the magnetic gradient induced coupling (MAGIC) scheme is emerging as a promising platform for quantum computing. Nevertheless, in this—as in any other—quantum-computing platform, many technical questions still have to be resolved before large-scale and error-tolerant applications are possible. In this work, we present a thorough discussion of the structure and effects

Elementary quantum mechanics proposes that a closed physical system consistently evolves in a reversible manner. However, control and readout necessitate the coupling of the quantum system to the external environment, subjecting it to relaxation and decoherence. Consequently, system-environment interactions are indispensable for simulating physically significant theories. A broad spectrum of physical

Subspace preserving quantum circuits are a class of quantum algorithms that, relying on some symmetries in the computation, can offer theoretical guarantees for their training. Those algorithms have gained extensive interest as they can offer polynomial speed-up and can be used to mimic classical machine learning algorithms. In this work, we propose a novel convolutional neural network architecture

Neural decoders for quantum error correction rely on neural networks to classify syndromes extracted from error correction codes and find appropriate recovery operators to protect logical information against errors. Its ability to adapt to hardware noise and long-term drifts make neural decoders promising candidates for inclusion in a fault-tolerant quantum architecture. However, given their limited

Feedback control of open quantum systems is of fundamental importance for practical applications in various contexts, ranging from quantum computation to quantum error correction and quantum metrology. Its use in the context of thermodynamics further enables the study of the interplay between information and energy. However, deriving optimal feedback control strategies is highly challenging, as it

We explore the energy content of superpositions of single-excitation current states. Specifically, we focus on the maximum energy that can be extracted from them through local unitary transformations. The figure of merit we employ is the local ergotropy. We consider an XY spin-chain model and perform a complete analysis in the whole range of the system parameters. This way, we prove that superpositions

We establish an information gain-disturbance trade-off relation in local state discrimination. Our result demonstrates a fundamental limitation of local strategy to discriminate entangled quantum states without disturbance, which becomes more difficult as the entanglement of the states to be discriminated increases. For a set of maximally entangled states (MESs), the capability of local strategy is

We report on the experimental measurement of the work statistics of a genuinely open quantum system using a quantum computer. Such measurement has remained elusive thus far due to the inherent difficulty in measuring the total energy change of a system-bath compound (which is the work) in the open quantum system scenario. We overcome this difficulty by applying the interferometric scheme, originally

We present a robust shadow estimation protocol for wide classes of low-depth measurement circuits that mitigates noise as long as the effective measurement map including noise is locally unitarily invariant. This is in practice an excellent approximation, encompassing for instance the case of ideal single-qubit Clifford gates composing the first circuit layer of an otherwise arbitrary circuit architecture

Information reconciliation (IR) is a crucial component in the post-processing stage of continuous-variable quantum key distribution (CV-QKD) systems. However, the requirement to process a large amount of information in IR has become the bottleneck of realizing high-throughput CV-QKD systems, and the phenomenon of classical channel overloads appears. To solve these issues, we first propose a lossy compression

Quantum optimal control theory (QOCT) can be used to design the shape of electromagnetic pulses that implement operations on quantum devices. By using non-trivially shaped waveforms, gates can be made significantly faster than those built by concatenating monochromatic pulses. Recently, we applied this idea to the control of molecular spin qudits modeled with Schrödinger’s equation and showed it can

The application of quantum algorithms to classical problems is generally accompanied by significant bottlenecks when transferring data between quantum and classical states, often negating any intrinsic quantum advantage. Here we address this challenge for a well-known algorithm for linear systems of equations, originally proposed by Harrow, Hassidim and Lloyd (HHL), by adapting it into a predictor–corrector

The interference between two independent photons stands as a crucial aspect of numerous quantum information protocols and technologies. In this work, we leverage fiber-coupled devices, which encompass fibered photon pair-sources and off-the-shelf optics, to demonstrate Hong-Ou-Mandel interference. We employ two distinct single photon sources, namely a heralded single-photon source and a weak coherent

A fast and scalable scheme for multi-qubit resetting in superconducting quantum processors is proposed by exploiting the feasibility of frequency-tunable transmon qubits and transmon-like couplers to engineer a full programmable superconducting erasing head. We demonstrate the emergence of collective effects that lead to a decoherence-free subspace during the erasing process. The presence of such a

Deep neural networks have demonstrated remarkable efficacy in extracting meaningful representations from complex datasets. This has propelled representation learning as a compelling area of research across diverse fields. One interesting open question is how beneficial representation learning can be for quantum many-body physics, with its notoriously high-dimensional state space. In this work, we showcase

Solving computational fluid dynamics (CFD) problems requires the inversion of a linear system of equations, which can be done using a quantum algorithm for matrix inversion (Gilyén et al 2019 Proc. 51st Annual ACM SIGACT Symp. on Theory of Computing 193–204). However, the number of shots required to measure the output of the system can be prohibitive and remove any advantage obtained by quantum computing

We propose using the dynamical invariants, also known as the Lewis–Riesenfeld invariants, to speed-up the equilibration of a driven open quantum system. This allows us to reverse engineer the time-dependent master equation that describes the dynamics of the open quantum system and systematically derive a protocol that realizes a shortcut to equilibration. The method does not require additional constraints

Photon-mediated dipole–dipole interactions arise from atom-light interactions, which are universal and prevalent in a wide range of open quantum systems. This pairwise and long-range spin-exchange interaction results from multiple light scattering among the atoms. A recent surge of interests and progresses in both experiments and theories promises this core mechanism of collective interactions as a

In broadband quantum optical systems, nonlinear interactions among a large number of frequency components induce complex dynamics that may defy heuristic analysis. In this work we introduce a perturbative framework for factoring out reservoir degrees of freedom and establishing a concise effective model (effective field theory) for the remaining system. Our approach combines approximate diagonalization

The simulation of molecular electronic structure is an important application of quantum devices. Recently, it has been shown that quantum devices can be effectively combined with classical supercomputing centers in the context of the sample-based quantum diagonalization (SQD) algorithm. This allowed the largest electronic structure quantum simulation to date (77 qubits) and opened near-term devices

Low loss and high-speed processing of photons is important to photonic quantum information technologies. The speed with which quantum light generation can be modulated impacts the clock rate of photonic quantum computers, the data rate of quantum communication and applications of quantum enhanced radio-frequency sensors. Here we use lossy carrier depletion modulators in a silicon waveguide nonlinear

Building scalable and secure quantum networks requires advanced quantum key distribution (QKD) protocols that support multi-user connectivity. Continuous-variable (CV) measurement-device-independent (MDI) QKD, which eliminates all detector side-channel attacks, is a promising candidate for creating various quantum network topologies-such as quantum access networks and star-type topologies-using standard

Due to their non-iterative nature, fixed unitary coupled cluster (UCC) ansätze are attractive for performing quantum chemistry variational quantum eigensolver (VQE) computations as they avoid pre-circuit measurements on a quantum computer. However, achieving chemical accuracy for strongly correlated systems with UCC requires further inclusion of higher-order fermionic excitations beyond triples increasing

Quantum direct coding or Schumacher compression generalised the ideas of Shannon theory, gave an operational meaning to the von Neumann entropy and established the term qubit. But remembering that information processing is carried out by physical processes prompts one to wonder what thermodynamic resources are required to compress quantum information and how they constrain one’s ability to perform

Open quantum many-body systems are of both fundamental and applicational interest. However, it remains an open challenge to simulate and solve such systems, both with state-of-the-art classical methods and with quantum-simulation protocols. To overcome this challenge, we introduce a simulator for open quantum many-body systems based on giant atoms, i.e. atoms (possibly artificial), that couple to a

We propose a novel optimization scheme designed to find optimally correctable subspace codes for a known quantum noise channel. To each candidate subspace code we first associate a universal recovery map, as if the code was perfectly correctable, and aim to maximize a performance functional that combines a modified channel fidelity with a tuneable regularization term that promotes simpler codes. With

Quantum computing holds transformative potential for various domains including cheminformatics through advancements in quantum algorithms. The key to realizing improvements with quantum algorithms in cheminformatics is encoding chemical data like proteins as quantum states with quantum state preparation. In this work, we propose a computational framework to encode proteins as quantum states for efficient

We present the first quantum computation of a total decay rate in high-energy physics at second order in perturbative quantum field theory. This work underscores the confluence of two recent cutting-edge advances. On the one hand, the quantum integration algorithm quantum Fourier iterative amplitude estimation, which efficiently decomposes the target function into its Fourier series through a quantum

We address the crucial role of noisy squeezing in security and performance of continuous-variable (CV) quantum key distribution (QKD) protocols. Squeezing has long been recognized for its numerous advantages in CV QKD, such as enhanced robustness against channel noise and loss, and improved secret key rates. However, the excess noise of the squeezed states, that unavoidably originates already from

Quantum annealing (QA) is a novel type of analog computation that aims to use quantum mechanical fluctuations to search for optimal solutions of Ising problems. QA in the transverse Ising model, implemented on D-Wave quantum processing units, are available as cloud computing resources. In this study we report concise benchmarks across three generations of D-Wave quantum annealers, consisting of four

High-dimensional time-frequency encodings have the potential to significantly advance quantum information science; however, practical applications require precise knowledge of the encoded quantum states, which becomes increasingly challenging for larger Hilbert spaces. Self-guided tomography (SGT) has emerged as a practical and scalable technique for this purpose in the spatial domain. Here, we apply

Optical frequency combs (OFCs) are paving the way for an unprecedented level of precision in synchronizing optical clocks over free-space. However, the conventional intensity-based strategy for estimating the timing offset between two OFCs is sub-optimal, whereas a strategy based on temporal modes can achieve the optimal precision bound under ideal conditions. In practice, the performance of both strategies

Since its advent in 2011, boson sampling has been a preferred candidate for demonstrating quantum advantage because of its simplicity and near-term requirements compared to other quantum algorithms. We propose to use a variant, called coarse-grained boson-sampling (CGBS), as a quantum proof-of-work (PoW) scheme for blockchain consensus. The miners perform boson sampling using input states that depend

Quantum data loading plays a central role in quantum algorithms and quantum information processing. Many quantum algorithms hinge on the ability to prepare arbitrary superposition states as a subroutine, with claims of exponential speedups often predicated on access to an efficient data-loading oracle. In practice, constructing a circuit to prepare a generic n-qubit quantum state typically demands

We study a chain of interacting individual quantum systems connected to heat baths at different temperatures on both ends. Starting with the two-system case, we thoroughly investigate the conditions for heat rectification (asymmetric heat transport), compute thermal conductance, and generalize the results to longer chains. We find that heat rectification in the weak coupling regime can be independent

Open quantum systems are susceptible to losses in information, energy, and particles due to their surrounding environment. One novel strategy to mitigate these losses is to transform them into advantages for quantum technologies through tailored non-Hermitian quantum systems. In this work, we theoretically propose a fast generation of multipartite entanglement in non-Hermitian qubits. Our findings

The possibility of extracting more work from a physical system thanks to the information obtained from measurements has been a topic of fundamental interest in the context of thermodynamics since the formulation of the Maxwell’s demon thought experiment. We here consider this problem from the perspective of an open quantum battery interacting with an environment that can be continuously measured. By

While gain-loss-coupled photonic platforms have achieved significant success in studying classical parity-time (PT) symmetry, they encounter challenges in demonstrating pure quantum effects due to incompatible operator transformations and Langevin noise. Here, we present compelling evidence that a non-Hermitian (NH) twin-beam system, undergoing phase-sensitive amplification and balanced loss, not only

Secure multi-party computation (SMPC) protocols allow several parties distrusting each other to collectively compute a function on their inputs, without revealing the input values. In this paper, we introduce a protocol that lifts SMPC to its quantum counterpart—secure multi-party quantum computation (SMPQC) for classical inputs and outputs—in a composable and statistically secure way, even for a single

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the relaxational quantum eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states

Heat transport in a qubit–oscillator junction described by the quantum Rabi model is investigated. Upon variation of temperature, bias on the qubit and the qubit–oscillator coupling strength, a rich variety of effects is identified. For weak coupling to bosonic heat baths, transport is essentially controlled by the qubit–oscillator coupling g which defines a Kondo-like temperature TK(g). At temperatures

Quantum key distribution (QKD) promises everlasting security based on the laws of physics. Most common protocols are grouped into two distinct categories based on the degrees of freedom used to carry information, which can be either discrete or continuous, each presenting unique advantages in either performance, feasibility for near-term implementation, and compatibility with existing telecommunications

In adiabatic quantum annealing, the speed with which an anneal can be run, while still achieving a high final ground state (GS) fidelity, is dictated by the size of the minimum gap that appears between the ground and first excited state in the annealing spectrum. To avoid the exponential slowdown associated with exponentially closing gaps, diabatic transitions to higher energy levels may be exploited

We propose a protocol for the preparation of generalized Greenberger–Horne–Zeilinger (GHZ) states of N atoms each with d = 3 or 4 internal levels. We generalize the celebrated one-axis twisting (OAT) Hamiltonian for N qubits to qudits by including OAT interactions of equal strengths between every pair of qudit levels, a protocol we call as balanced OAT (BOAT). Analogous to OAT for qubits, we find that

Quantum thermometry refers to the study of measuring ultra-low temperatures in quantum systems. The precision of such a quantum thermometer is limited by the degree to which temperature can be estimated by quantum measurements. More precisely, the maximal precision is given by the inverse of the quantum Fisher information. In the present analysis, we show that quantum thermometers that are described

Cavity-modified chemistry uses strong light-matter interactions to modify the electronic properties of molecules in order to enable new physical phenomena such as novel reaction pathways. As cavity chemistry often involves critical regions where configurations become nearly degenerate, the ability to treat multireference problems is crucial to understanding polaritonic systems. In this Letter, we show

Complex quantum circuits are constituted by combinations of quantum subroutines. The computation is possible as long as the quantum data encoding is consistent throughout the circuit. Despite its fundamental importance, the formalization of quantum data encoding has never been addressed systematically so far. We formalize the concept of quantum data encoding, namely the format providing a representation

Distributing quantum correlations to each node of a network is a key aspect of quantum networking. Here, we present a robust, physically motivated protocol by which global quantum correlations, as characterized by the discord, can be distributed to quantum memories using a mixed state of information carriers which possesses only classical correlations. In addition, such distribution is done using only

Light-pulse atom interferometers based on single-photon transitions are a promising tool for gravitational-wave detection in the mid-frequency band and the search for ultralight dark-matter fields. Here we present a novel measurement scheme that enables their use as freely falling clocks directly measuring relativistic time-dilation effects. The proposal is particularly timely because it can be implemented

We study the identification of quantum phases of matter, at zero temperature, when only part of the phase diagram is known in advance. Following a supervised learning approach, we show how to use our previous knowledge to construct an observable capable of classifying the phase even in the unknown region. By using a combination of classical and quantum techniques, such as tensor networks, kernel methods

Computing nonlinear functions over multilinear forms is a general problem with applications in risk analysis. For instance in the domain of energy economics, accurate and timely risk management demands for efficient simulation of millions of scenarios, largely benefiting from computational speedups. We develop a novel hybrid quantum–classical algorithm based on polynomial approximation of nonlinear

Despite the complexity of quantum systems in the real world, models with just a few effective many-body states often suffice to describe their quantum dynamics, provided decoherence is accounted for. We show that a machine learning algorithm is able to construct such models, given a straightforward set of quantum dynamics measurements. The effective Hilbert space can be a black box, with variations

The prediction of electronic structure for strongly correlated molecules represents a promising application for near-term quantum computers. Significant attention has been paid to ground state wavefunctions, but excited states of molecules are relatively unexplored. In this work, we consider the adaptive, problem-tailored (ADAPT)-variational quantum eigensolver (VQE) algorithm, a single-reference approach

Low-loss high-speed switches are an integral component of future photonic quantum technologies, with applications in state generation, multiplexing, and the implementation of quantum gates. Phase modulation is one method of achieving this switching; however, existing optical phase modulators offer either high bandwidth or low loss—not both. We demonstrate fast (100 MHz bandwidth), low-loss ( 83(2)%