213 curated articles
Quantum processors with native multi-qubit gates may offer very efficient implementations of near-term quantum algorithms on noisy hardware. Here, we introduce the multiunimon, a superconducting multimode circuit that encodes multiple qubits and enables native multi-qubit gates in a device consistin...
The authors present a rigorous empirical evaluation of three distinct optimization paradigms for institutional factor portfolio construction: an entro...
Quantum technology has the potential to transform scientific discovery, but quantum advantages often require processing capabilities well beyond the r...
Unitary designs provide finite-moment approximations to Haar-random unitaries, with wide-ranging applications across physics and quantum information, ...
Photonic quantum computing developer Xanadu Quantum Technologies Limited (NASDAQ/TSX: XNDU) has announced a strategic research partnership with the Un...
Ensuring ancilla safety is a critical correctness requirement for quantum compilation, since ancilla qubits are routinely introduced to implement comp...
From fluid flow and transport to collective dynamics, numerical simulation of nonlinear partial differential equations underpins modern scientific com...
As quantum computing progresses from proof-of-principle demonstrations toward practical utility, a significant impediment is the need to augment algor...
Scientific simulations demand methods combining scalability with predictive accuracy. Density Functional Theory (DFT) on High-Performance Computing (H...
When quantum information initially stored in a local qubit disappears, it need not be lost: it may have moved into nearby degrees of freedom or become...
Quantum advantage refers to the point at which a quantum computer solves a clearly defined task faster or more efficiently than any classical computer...
Quemix Inc., a Tokyo-based quantum software and algorithm startup and consolidated subsidiary of TerraSky Co., Ltd., announced it has secured an inves...
Generating entanglement rapidly and reliably is essential for quantum information processing, communication, and metrology. Dissipative preparation is...
This paper investigates a quantum extension of classical Multiple-Input Multiple-Output (MIMO) communication in which the conventional linear channel ...
Distributed quantum computing provides a scalable route for executing quantum circuits beyond the capacity limits of a single quantum processing unit ...
This paper aims to contextualize the requirements for Quantum Computing (QC) algorithms to achieve a quantum advantage in solving the alternating curr...
Shor's algorithm is a canonical quantum supremacy target whose core operation relies on the Quantum Fourier Transform (QFT). We resolve an open questi...
Xanadu Quantum Technologies Ltd. (NASDAQ/TSX: XNDU) has announced its financial results for the second quarter ended June 30, 2026. The Toronto-based ...
Insider Brief A preliminary paper from an Amazon Web Services cryptographer describes a polynomial-time quantum algorithm for a long-standing mathemat...
Quantum optimization has attracted growing interest as quantum hardware continues to improve, yet state-of-the-art classical solvers remain a formidab...
Solving the Vehicle Routing Problem (VRP) in Stochastic Transportation Networks (STNs), a core task in Intelligent Transportation Systems (ITS), intro...
Mapping quantum programs to restricted physical chips requires SWAP operations, incurring depth and error penalties. In symmetric programs, this routi...
This post was contributed by Martin Schuetz and Ruben Andrist from the Amazon Advanced Solutions Lab, and Romina Yalovetzky and Atithi Acharya from Gl...
Extracting total correlations from a quantum system usually requires reconstructing its state, whereas many experiments access only a few measurement ...
Dynamic quantum circuits (DQCs) provide a hardware-efficient route to quantum computing by reducing physical-qubit overhead and compressing circuit to...
Hamming weight computation maps an $n$-bit input to the number of ones it contains. It is a basic subroutine in quantum computing, and the core buildi...
Partial dynamical symmetry (PDS) is an algebraic structure in which a prescribed symmetry is neither exact nor completely broken: a subset of eigensta...
Tensor-network contraction simulates quantum circuits, but modern matrix accelerators (NPUs, TPUs) expose only real GEMM pipelines, so the complex net...
Quantum error correction (QEC) is indispensable for building scalable fault-tolerant quantum computers. Effective QEC demands stringent real-time deco...
Quantum error correction (QEC) and Quantum Darwinism describe opposing consequences of system-environment interactions: QEC seeks to preserve logical ...
Insider Brief Press release – According to the 2026 Thales Data Threat Report, the threat of Harvest Now, Decrypt Later (HNDL) attacks was the top-cit...
Insider Brief Jim Cramer said he plans to sell his bitcoin — perhaps not coincidentally — after IBM Chairman and CEO Arvind Krishna warned that invest...
This study investigates the generation and enhancement of quantum entanglement in an electro-optomechanical ring cavity system. The setup integrates t...
Quantum algorithms based on linear-system approaches for solving differential equations demand qubit and precision resources beyond near-term capabili...
Photonic multi-qubit entanglement is key to optical quantum information processing, particularly universal quantum computing. Yet multi-photon sources...
We investigate a quantum Otto engine (QOE) constructed from the two-qubit quantum Rabi model, operating within a cavity quantum electrodynamics (QED) ...
Quantum resource theory has sharpened our understanding of the intrinsic complexity of quantum systems, particularly their classical simulability. How...
Many-body localization (MBL) is a dynamical phenomenon that describes the non-ergodicity of isolated quantum many-body systems. In contrast to thermal...
Insider Brief Press release – SEALSQ Corp (NASDAQ: LAES) (“SEALSQ” or the “Company”), a global leader in post-quantum semiconductor and cybersecurity ...
Most recently proposed quantum algorithms for solving linear and nonlinear partial differential equations rely on non-unitary operations. These operat...
In spite of recent advances, quantum computers are expected to be sufficiently noisy in the coming few years to the extent of limiting quantum chemica...
This paper proposes a multi ring M-APSK constellation optimization method for discrete-modulated continuous variable quantum key distribution. Unlike ...
Superconducting quantum computer developer IQM Quantum Computers (Nasdaq: IQMX) and European rail operator Deutsche Bahn have published joint research...
Qubit loss occurs when the physical carrier of a qubit leaves the computational system without directly revealing the event's location. Such errors ar...
The proliferation of power electronics in multi-terminal transmission grids has increasingly led to harmonic distortions and dynamic instabilities. Wh...
Quantum error correction (QEC) codes can correct twice as many erasure errors as Pauli errors. Because of this scaling advantage, there is significant...
Insider Brief The post-quantum conversation has focused heavily on which algorithms to adopt, but algorithm selection is the second problem, not the f...
Silicon-based donor flip-flop qubits offer a promising path toward scalable, fault-tolerant quantum computing by combining the long coherence times of...
IBM and a coalition of research collaborators—including the University of Chicago, Qedma Quantum Computing, Algorithmiq, RIKEN, and BlueQubit—have ann...
As quantum computing matures, it is critical to benchmark its real-world problem solving performance against competitive classical methods, such as te...
We develop a hybrid qubit--qumode algorithm for nonlinear ordinary differential equations of the form $\dot{\mathbf{x}}=\mathbf{f}(\mathbf{x})$ with d...
Analog quantum processors based on Rydberg atom arrays are a powerful platform for many-body quantum simulation, combinatorial optimization, and graph...
Optimization problems are among the leading candidates for industrially relevant quantum advantage. Decoded quantum interferometry (DQI) has been prop...
Insider Brief Researchers from Quantinuum, NVIDIA and Pfizer have developed an artificial intelligence system that learns to generate quantum circuits...
Topological data analysis (TDA) provides a powerful framework for extracting information about the shape of complex, unstructured data, but the classi...
Modular quantum computing is a leading paradigm for scaling quantum computation beyond the resource limitations of monolithic devices. In this archite...
The Non-Equilibrium Green's Function (NEGF) is the standard formalism for nano-scale electron transport. By recasting the NEGF scattering problem as a...
We demonstrate an end-to-end hybrid quantum-classical optimisation framework based on Benders decomposition, capable of solving mixed-integer linear p...
The dynamics of a nuclear spin bath generates magnetic noise that is a key contributor to the decoherence of electron spin qubits in electrostatically...
Quantum computers are moving from research laboratories to industrial machines accessible via the cloud and integrated into high-performance computing...
Mapping quantum phase diagrams through classical simulation is notoriously resource-intensive, as even small systems far from the thermodynamic limit ...
Passive linear optics is a restricted model of quantum computation, with complexity-theoretic evidence of quantum advantage for sampling tasks and low...
Optimal control problems arise in a wide range of scientific disciplines, but the corresponding optimization algorithms often display a strong depende...
Variational quantum algorithms offer a promising route to combinatorial optimization, but their applicability is limited by the challenge of encoding ...
Variational quantum circuits have been central to many proposed near-term applications of quantum computing, but a growing body of evidence suggests t...
Completely positive (CP) matrices are ubiquitous in modern science and technology with applications in optimization, graph theory, and quantum entangl...
Telecommunications leader AT&T (NYSE: T) has signed a commercial agreement with D-Wave Quantum Inc. (NASDAQ: QBTS) to expand its use of quantum anneal...
Quantum software provider Qedma has announced a technical integration with Quantinuum, making its Quantum Error Suppression and Error Mitigation (QESE...
Quantum state preparation is a key component of many quantum algorithms. Performing this step efficiently is essential for realizing practical quantum...
This is a short study of an approach offering high tolerance to damage (i.e. defects or 'drop outs') in solid state fault-tolerant quantum computing. ...
We introduce Quantum-Informed Surrogate Sampling (QISS), a post-processing framework that generates candidate solutions to combinatorial optimization ...
To maximize the value of fault-tolerant quantum computers, it is essential to develop concrete applications beyond well-established domains such as ch...
Entanglement purification protocols (EPPs) are essential for improving entanglement fidelity to support fault-tolerant distributed quantum information...
We present a strategic plan for neutral atom quantum computation, bringing together hardware development and theory advancements to achieve the goal o...
Variational quantum algorithms are a leading approach to near-term quantum computing, but their scalability can be limited by barren plateaus and the ...
Formal verification is becoming increasingly practical for quantum computing, yet the ability of AI agents to construct machine-checkable proofs in th...
Financial fraud detection is challenged by decentralized data, severe class imbalance, and privacy constraints. This paper presents QuantumChain, a se...
Recent experiments on quantum computers have challenged the limits of classical computation in chemistry, simulating ground states of strongly correla...
We propose a protocol for preparing mechanical Schrödinger kittens -- mesoscopic quantum superpositions of coherent motional states of an optically le...
Insider Brief PRESS RELEASE — Quantinuum (NASDAQ: QNT) and SoftBank Corp. (“SoftBank”) today announced the publication of “Quantum Computing Frontiers...
The Variational Quantum Eigensolver (VQE) is a leading algorithm for estimating molecular ground-state energies on near-term quantum hardware, with ap...
The Dicke model provides a fundamental description of collective light-matter interactions and has long served as a testbed for exploring a wide range...
This post was contributed by Dimitar Trenev, Sebastian Stern, Tyler Takeshita, Cedric Lin, Peter Komar, Pooja Rao, Jerome Gonthier, and Elica Kyoseva....
Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, combining parameterized quantum circuits with classical ...
Circuit cutting promises to scale quantum computations beyond current hardware, but variational quantum advantage also requires low cutting overhead, ...
Pauli-based simulators offer a promising route to large-scale classical simulation of quantum circuits in the low-magic regime. Yet their applicabilit...
We provide a formal framework for Continuous-Variable Quantum Computing (CQC). While CQC is supported by photonic quantum hardware, we are not aware o...
Quantum machine learning on real noisy intermediate-scale quantum (NISQ) hardware has remained largely confined to binary or few-class tasks, limited ...
Quantum key distribution (QKD) over non-stationary channels, such as satellite links, is characterized by short, high-loss, and strongly fluctuating t...
Insider Brief PRESS RELEASE — IQM Quantum Computers (Nasdaq: IQMX), a global leader in full-stack superconducting quantum computers, today published t...
We develop a sparse operator-centric realization of $n$-qubit variational quantum algorithms in the complex Clifford algebra $\mathrm{Cl}(2n,\mathbb{C...
The UK's deep-tech innovation accelerator Digital Catapult has welcomed 11 commercial and public organizations to the third cohort of its Quantum Tech...
While quantum computers promise to solve classically intractable problems, identifying the point at which fault-tolerant quantum computation outperfor...
The Variational Quantum Eigensolver (VQE) and its adaptive variants, such as ADAPT-VQE, are central to the study of strongly correlated quantum system...
Insider Brief PRESS RELEASE — A truly useful quantum computer must be able to run any algorithm at all, with the same versatility an ordinary laptop o...
Neutral-atom arrays and trapped-ion crystals offer complementary strengths for fault-tolerant quantum computing but lack a fast way to deterministical...
Learning a classical description of a quantum state is a fundamental task in quantum computation. Among the most important classes of quantum states a...
Alternating Current Optimal Power Flow Unit Commitment (AC-OPF-UC) is a difficult mixed-integer nonlinear optimization problem that combines binary ge...
We characterize and compare the inherent interpretability offerings of a standard linear model with a single qubit mixed state model for the task of s...
Subspace Quantum Diagonalization (SQD) recovers ground-state energies by classically diagonalizing a Hamiltonian in the subspace spanned by quantum sa...
Exact fermion to qubit transformations are conventionally regarded as algorithmic tools that translate many-body Hamiltonians into qubit representatio...
The Navascués-Pironio-Acín (NPA) hierarchy provides a convergent sequence of semidefinite programming (SDP) relaxations for noncommutative polynomial ...
The International Organization for Standardization (ISO) has officially integrated the Classic McEliece algorithm into its asymmetric cipher standard ...
Based on a photonic computing platform, we experimentally validate a generalized variational quantum linear solver (VQLS) by systematically solving fo...
Hybrid continuous-discrete-variable quantum processors can represent bosonic degrees of freedom directly in oscillator modes, or qumodes, while using ...
The Elliptic Curve Discrete Logarithm Problem (ECDLP) is a fundamental problem in cryptography, and reducing the resource requirements of quantum algo...
Insider Brief Press release – It’s proven that today’s encryption is vulnerable to attack by a sufficiently mature quantum computer running Shor’s alg...
Quantum algorithms solve certain computational problems faster than the best known classical algorithms. Many algorithms, including Shor's for factori...
Rotational irrigation scheduling in water-scarce Central Asia is a densely coupled combinatorial problem: soil-moisture memory links each irrigation d...
Parameterized quantum circuits~(PQCs) constitute a central building block of variational quantum algorithms~(VQAs) and quantum machine learning~(QML) ...
Neutral-atom quantum processors are rapidly scaling toward system sizes of more than ten thousand qubits, allowing for the realization of a new class ...
A central model in quantum machine learning is the quantum neural network (QNN), whose design requires balancing expressivity and trainability. Techni...
This article explores the potential of Quantum Machine Learning (QML), specifically assessing a Quantum Support Vector Machine (QSVM) and a Variationa...
We present a variational quantum framework for finite-horizon quantum control based on hardware-efficient ansätze. The objective is to steer a quantum...
Quantum circuit optimization for fault-tolerant computing requires exact functional equivalence while minimizing expensive non-Clifford resources such...
Quantum PDE solvers are difficult to evaluate in practice because published studies use different discretizations, output models, reconstruction rules...
Physics-informed neural networks (PINNs) provide a pathway to reunify the simulation and control of quantum systems, in which these two tasks are typi...
Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing. However, ...
Quantum computing has advanced rapidly in recent decades, driven by developments across the technology stack, including quantum error-correcting codes...
Reliable qubit readout is a critical bottleneck toward fault-tolerant quantum computing (FTQC). In superconducting quantum processors, readout operati...
Despite rapid progress in quantum optimization, broad real-hardware benchmarks comparing multiple algorithmic families across diverse combinatorial pr...
Gate-based digital quantum simulations offer an exciting new paradigm for studying the many-body physics of strongly correlated systems. In this conte...
Neutral Atom Quantum Computing (NAQC) is an emerging modality for scalable quantum computation, valued for its long coherence times and the naturally ...
We investigate the use of variational quantum algorithms to prepare and characterize fractional quantum Hall states on near-term quantum processors. F...
The short Doppler-limited coherence time of the laser-excited Rydberg state, usually orders of magnitude shorter than the lifetime of the Rydberg stat...
Distributed quantum computation needs to move logical qubits across lossy optical links, yet this transmission layer is usually designed separately fr...
International research networks and academic sponsors have opened competitive application windows targeting immediate software optimizations for early...
Reinforcement learning uses error information to adjust control algorithms.
Insider Brief Google is seeking university researchers to help solve two of quantum computing’s most immediate challenges, launching academic funding ...
Insider Brief PRESS RELEASE — INQUBATOR, Fraunhofer’s quantum computing consulting and testing center, offers businesses an practical and cost-effecti...
We perform a semiclassical, large-spin S, analysis of the quantum approximate optimization algorithm (QAOA) on the Sherrington-Kirkpatrick (SK) model,...
Grokking, the delayed transition from memorization to generalization, is a fundamental phenomenon in gradient-based learning, yet its dynamics within ...
The nuclear shell model is a general way of expressing the many-body nuclear Hamiltonian and deciphering the underlying nuclear structure. In today's ...
The emergence of Quantum Software Engineering (QSE) responds to the need for systematic, disciplined, and quantifiable approaches to the development, ...
Designing fault-tolerant quantum circuits that are both algorithmically correct and hardware compatible remains a major bottleneck in the transition t...
The performance of variational quantum algorithms depends in general on the structure of the parametrized quantum circuit, but the most common ansätze...
This short report explores the (non exhaustive) current state of quantum technologies, their potential applications, and the challenges that must be a...
Given that quantum computers are naturally suited to simulate the behavior of quantum many-body systems, an immediate question arises: can one formula...
Parameterized quantum circuits (PQCs) are increasingly used as policies and value functions in quantum reinforcement learning, yet it remains unclear ...
Tile codes are a family of planar quantum low-density parity-check (qLDPC) codes with weight-6 stabilizers and open boundary conditions, offering an e...
Nonlinear differential equations play a crucial role in modeling a wide range of phenomena, yet their solutions remain notoriously difficult to obtain...
Circular states in Rydberg atoms offer a promising platform for quantum computation, quantum simulation and quantum sensing. However, the final step o...
Transversal logical gates provide a direct route to fault-tolerant quantum computation, but the Eastin-Knill theorem forbids a universal transversal g...
Insider Brief Researchers have demonstrated a hybrid quantum-classical approach to portfolio optimization that solved real-world financial optimizatio...
The contraction coefficient of the trace distance is a central tool in quantum information, quantifying how strongly a quantum channel degrades the di...
Quantum machine learning (QML) could have the potential to leverage advantages of quantum over classical computing but still lacks strong evidence of ...
Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks o...
IBM Quantum has released a technical review detailing the initial research outcomes generated by its expanded IBM Quantum Credits program. Spearheaded...
IBM Chairman and Chief Executive Officer Arvind Krishna has confirmed that the greenfield city of Amaravati will host one of the first two physical IB...
Insider Brief Press release – QoreChain, a quantum-safe, AI-native Layer 1 blockchain, has recorded what it describes as the first transaction in the ...
Insider Brief Press release – XDots (xDots), a company specializing in quantum technology-based energy optimization solutions, participated in Quantum...
We study stabilizer state testing and learning with limited coherent quantum memory. Here an algorithm sequentially receives copies of an unknown $n$-...
Quantum Error Recovery (QER) uses knowledge of the error channel acting on a quantum system to find optimal recovery maps. The scheme restores the unc...
Quantum convolutional neural networks (QCNNs) have become increasingly popular in quantum machine learning (QML) due to their efficient parameterizati...
In the NISQ era, there is a need for resource-efficient proof-of-principle experiments that can be built up to genuine utility. Single-qubit classifie...
Block encodings are a central primitive in quantum algorithms, but standard constructions typically require logarithmic ancilla overhead and complicat...
We study the compilation of structured quantum gate families on two-dimensional neutral-atom arrays, aiming to reduce addressing and transport overhea...
WiMi Hologram Cloud Inc. (NASDAQ: WiMi) has announced ongoing research into the utilization of machine learning models to optimize operational paramet...
The transverse-field Ising model has attracted a lot of attention in recent years, especially in the quantum simulation and quantum computation litera...
Portfolio diversification - a cornerstone of modern investment management - can be formulated as a Maximum Independent Set (MIS) problem on asset corr...
Realizing quantum neural networks (QNNs) in industry requires knowing which quantum computing paradigm suits which task. Motivated by AI accelerators ...
We give an analytical expression for the dynamical Lie algebra corresponding to the QAOA-MaxCut problem on complete graphs, and show that the variance...
Insider Brief A new AI-assisted framework may help researchers find useful patterns in quantum algorithms before they spend scarce time running them o...
Adaptive Derivative-Assembled Problem-Tailored variational quantum eigensolvers (ADAPT-VQE) represent one of the most promising approaches for quantum...
Multi-core quantum computing architectures have emerged as a promising solution to the qubit scalability limitations of monolithic NISQ devices. Quant...
Silicon spin qubits are promising for large-scale quantum-computer integration because they can fully leverage the well-developed semiconductor infras...
As Quantum Machine Learning (QML) transitions toward practical implementation, the field faces a critical architectural bottleneck that challenges the...
Practical hardware limitations, including finite transmitter and receiver filter lengths as well as the finite resolution of digital-to-analog and ana...
We introduce a hybrid approach utilising a quantum machine learning surrogate model to approximate the non-linear collision dynamics of the LBM. It ef...
Remarkable technical progress has made high-rate, high-distance, quantum low-density parity-check codes (QLDPC) promising candidates for scalable quan...
Measurement-based quantum computing is a universal model of quantum computation in which successive product measurements of an entangled resource stat...
Over the past decades, the operations research community has developed numerous effective optimization algorithms, yet quantum computing is emerging a...
The universal scaling of critical behavior in phase transitions is a cornerstone of physics. Dynamical quantum phase transitions (DQPTs) are their non...
Universal blind quantum computation (UBQC) hides a client's computation by using a computation-independent BFK09 brickwork graph and encoding the comp...
Bosonic hardware developer Alice & Bob has published a computer architecture blueprint authored by senior architect Kevin D. Kissell detailing a new "...
Advanced technological holding company Quantum X Labs Inc. (Nasdaq: QXL) has announced the launch of an integrated quantum software development progra...
We extend Noise-Directed Adaptive Remapping (NDAR), a recently proposed heuristic meta-algorithm that leverages device noise as a computational resour...
Variational excited-state quantum algorithms fail for reasons usually studied in isolation: barren plateaus, symmetry contamination, finite-sampling i...
Cavity optomechanical systems have emerged as a promising platform for quantum sensing. Quantum mechanics imposes a standard quantum limit (SQL) on th...
Achieving high-fidelity execution on noisy intermediate-scale quantum (NISQ) hardware requires careful selection of physical qubit layouts, as gate er...
Trapped-ion systems have emerged as a leading platform for scalable quantum information processing owing to their high-fidelity operations and long-ra...
Graphs provide a natural language for relational data in chemistry, biology and optimisation. Graph neural networks (GNNs) have driven much of the rec...
Quantum neural networks have emerged as powerful models for approximating nonlinear functions. Yet their use in solving integro-differential equations...
Classiq and technology company TEA TEK Group have announced a strategic partnership to establish a quantum computing hub in Naples, Italy. The facilit...
Autoencoders transformed classical machine learning by solving the curse of dimensionality, enabling principled weight initialization and learning com...
Realizing coherent quantum computation requires precise and robust manipulation of quantum systems through quantum control protocols. Most quantum con...
Useful quantum algorithms require many coupled discrete design choices. We study LLM-driven evolutionary program synthesis -- a language model edits a...
We present the analytical generators for arbitrary multi-qubit controlled gates. Closed forms for the generating Hamiltonians are given for gates with...
Insider Brief PRESS RELEASE — Quantum Elements and USC today announced the publication of a new Quantum Monte Carlo algorithm in Physical Review Lette...
Quantum low-density parity-check (qLDPC) codes are promising candidates for realizing large-scale fault-tolerant quantum computing. Although many code...
Multi-qubit systems are essential for scalable quantum technologies, but their performance is often limited by decoherence from qubit--qubit interacti...
Yuval Boger interviews Helmut Katzgraber, general partner at 55North and former quantum leader at AWS. They discuss Helmut’s view that the most promis...
We present an efficient protocol for learning an unknown $k$-local Lindblad generator on $n$ qubits using only product-state preparations, short-time ...
We provide a pre-obfuscation circuit-level implementation of an efficient one shot signature scheme, which has known applications to delegated signatu...
Insider Brief PRESS RELEASE — Fixstars Amplify Corporation (President and CEO: Yoshiki Matsuda) is pleased to announce the addition of the IonQ quantu...
The Learning With Errors (LWE) problem constitutes the mathematical foundation of modern Post-Quantum Cryptography (PQC). Cryptanalysis of LWE ranges ...
Quantum platforms with beyond-planar connectivity provide new opportunities for fault-tolerant quantum computation (FTQC). While quantum low-density p...
Independent researchers from the IBM Quantum Network have published two separate technical studies validating real-world applications on the IBM Night...
Cloud-based optimization developer Fixstars Amplify Corporation has added IonQ’s trapped-ion quantum computing environment as a standard execution bac...
Insider Brief The majority of the conversations about quantum computing focus on hardware and the software side gets less attention, but it is where m...
The University of Southern Denmark (SDU) has partnered with hardware developer Quantinuum and the Danish e-Infrastructure Consortium (DeiC) to integra...
We study the problem of learning local Lindbladians from black-box access to the physical evolution, and the goal is to estimate all Hamiltonian and d...
We present a systematic study of von Neumann entropy estimation in multi-qutrit quantum systems using two complementary approaches: variational quantu...
Neutral atom quantum computers (NAQC) are emerging as a promising, scalable quantum computing platform because of their long qubit coherence, flexible...
High-harmonic generation (HHG) is governed by interference between electron trajectories. We propose that the dominant short and long trajectories def...
The success of variational quantum learning models crucially depends on choosing parametrizations that reflect the structure of the problem at hand. S...
Estimating nonlinear properties of quantum states is a central task in quantum information science. Multivariate traces, $\mathrm{tr}(ρ_1 \cdots ρ_K)$...
Quantum spin glasses are often considered testbeds for studying quantum optimization algorithms and as such have been the subject of various quantum a...
An efficient implementation of quantum algorithms is often hindered by the lack of efficient primitives for operators and state preparation. This limi...
We present the Grover adaptive search self-consistent field (GAS-SCF) algorithm. GAS-SCF leverages quantum arithmetic to construct an efficient oracle...
We report the first results of the magnetic dipole hyperfine structure (HFS) constants of neutral $\mathrm{Li}$, Li-like $\mathrm{Be}$, neutral $\math...
For quantum algorithms to achieve their full potential, we need methodologies to optimize them, such as reaching a given output accuracy with minimal ...
Continued advancements in quantum computing have stimulated growing interest in translating quantum technologies into real-world applications. Consequ...