203 curated articles
The classical simulation of quantum algorithms is a crucial tool for circuit development, testing, and validation. Although acceleration using GPUs significantly reduces simulation time, most high-performance simulators rely on vendor-specific frameworks that target data-center hardware. To broaden ...
How much energy does a quantum computer consume? Are they more efficient than their classical counterparts? In this work, we make a step towards answe...
Positive maps that are not decomposable are a key resource in entanglement theory because they can detect bound entangled states, yet systematic metho...
Variational quantum algorithms (VQAs) are a central paradigm for noisy intermediate-scale (NISQ) quantum computing, yet their reliance on predesigned ...
A quantum compiler is a critical piece in the quantum computing pipeline since it allows an abstract quantum circuit to be run on a physical quantum c...
A new quantum-inspired algorithm has cracked a problem so massive that conventional supercomputers struggle to even approach it. Researchers used the ...
Hybrid quantum--classical pipelines increasingly support applications such as drug discovery, fraud detection, and cloud quantum processing unit (QPU)...
The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-...
We consider the multi-qubit fixed-excitation state transfer along the spin chain with dipole-dipole interaction subjected to the interaction with envi...
Quantum information platforms enable analog quantum simulations, such as quantum annealing, offering a promising route to solving complex combinatoria...
Quantum key distribution (QKD) promises information-theoretic security based on quantum mechanics and idealized device models. Practical implementatio...
Measurement-based quantum computing uses measurement patterns on predefined quantum resource states to execute quantum logic. Quantum simulation offer...
We study exact-regenerating codes for entanglement-assisted distributed storage systems. Consider an $(n,k,d,α,β_{\mathsf{q}},B)$ distributed system t...
Quantum computation holds the promise of solving certain complex problems exponentially faster than classical computers. However, the high prevalent n...
Insider Brief PRESS RELEASE — Quobly, a French pioneer in silicon-based quantum computing, and Taiwan’s Hon Hai Research Institute, the R&D arm of Hon...
Quantum error correction (QEC) is essential for enabling quantum advantages, with decoding as a central algorithmic primitive. Owing to its importance...
Barren plateaus in variational quantum circuits are commonly attributed to strong mixing dynamics that cause gradient variance to vanish exponentially...
Insider Brief PRESS RELEASE — Quantum software company Algorithmiq has established Milan as its global headquarters, signalling its confidence and com...
The measurement of top-quark spin correlations provides a key tool for probing its interactions with high precision. Owing to its extremely short life...
We report on a gate-based variational quantum classifier implemented with single photons and probabilistic gates, to emulate the standard quantum circ...
We introduce Unitaria, a Python library that brings the simplicity of classical linear algebra toolkits such as NumPy and SciPy to the implementation ...
The scalability of quantum computing is currently limited by physical, technological, and architectural constraints that hinder the integration of a l...
Insider Brief PRESS RELEASE — New York University and IBM have initiated a postdoctoral program to conduct quantum computer research in the areas of c...
In this paper, we present SCALAR (Symbolic Conjecture and LLM-Assisted Reasoning), a neurosymbolic framework for automated conjecture generation in qu...
Variational quantum algorithms have attracted attention for their potential to solve combinatorial optimization problems. We study how the choice of e...
Yuval Boger interviews Scott Aaronson, a UT Austin computer science professor known for his work on quantum computing theory. They explore the current...
Insider Brief Governments are establishing timelines for the transition to post-quantum cryptography, with requirements extending beyond public sector...
Quantum simulation has begun to penetrate the field of quantum chemistry in hopes of efficiently calculating ground state energies and approximating r...
Insider Brief PRESS RELEASE — Quandela and Safran Tech, Safran’s research and technology centre, have announced the launch of the AQeFLU research proj...
Variational quantum circuits with angle encoding implement truncated Fourier series, and architectures arranging $N$ qubits with $L$ encoding layers e...
In the domain of variational quantum algorithms, quantum Fourier models (QFMs) provide a mathematically well defined structure for quantum machine lea...
Insider Brief PRESS RELEASE — What do cars, bridges and airplanes have in common? They are all exposed to the open air most of the time and are subjec...
We address the circuit-design problem of maximizing quantum magic in early fault-tolerant quantum computing (early FTQC), where logical dynamics nativ...
Neutral atom platforms are analogue quantum simulators that offer the possibility to map graphs onto a 2D qubit register using programmable Rubidium a...
Graph embedding is a recurrent problem in quantum computing, for instance, quantum annealers need to solve a minor graph embedding in order to map a g...
Deep reinforcement learning (DRL), acting as a novel and powerful paradigm for quantum optimal control, offers transformative opportunities for advanc...
Quantum Art, an Israeli trapped-ion quantum computing company, has announced the successful completion of a joint project with a leading Israeli gover...
We report experimental digital quantum simulation of the one-dimensional Fermi-Hubbard model on a superconducting quantum processor at a scale beyond ...
We revisit the reduction of Cheng and Wan, which transforms instances of the discrete logarithm problem (DLOG) over finite fields into a decoding prob...
Shor's algorithm is one of the most promising applications of quantum computers. However, since $\sim 10^6$ physical qubits are believed to be require...
The quantum internet aims to interconnect distant devices and enable large-scale computation through distributed quantum algorithms. One of the key ob...
Pauli-based computation (PBC) provides a universal framework for executing fault-tolerant quantum algorithms using Pauli measurements and magic states...
The computation of quantum entanglement can be formulated as a high-dimensional nonconvex optimization problem with orthogonality constraints. In this...
On noisy intermediate-scale quantum (NISQ) devices, expectation values of many observables are obtained through sampling-based approximations to trace...
Insider Brief PRESS RELEASE — Quantum Art, an Israeli trapped-ion quantum computing company providing full-stack solutions, today announced the result...
We propose a quantum multi-level estimation framework for a functional $\sum_{i=1}^n f(p_i)$ of a discrete distribution $(p_i)_{i=1}^n$. We partition ...
Distributed quantum algorithms offer a promising pathway to scale variational quantum algorithms beyond the constraints of noisy intermediate-scale qu...
In this article, we take a close look at Entropy Quantum Computing (EQC), a computational paradigm developed by Quantum Computing Inc. (QCi), which de...
Quantum machines are among the most promising technologies expected to provide significant improvements in the following years. However, bridging the ...
Among the limitations of current quantum machines, the qubits count represents one of the most critical challenges for porting reasonably large comput...
Insider Brief The encryption protecting most of the internet is expected to become vulnerable to sufficiently advanced quantum computers. RSA and elli...
Insider Brief PRESS RELEASE — Magnons are tiny waves in magnetisation and ideal building blocks for hybrid quantum systems and quantum metrology. Howe...
The cascaded variational quantum eigensolver (CVQE) circumvents the need for iterative communication between the quantum and classical processing unit...
The Traveling Salesman Problem (TSP) is a prototypical combinatorial optimization problem, but its quantum implementation is limited by the O(n^2)-qub...
Attaining a quantum speedup in solving practically useful optimization problems has been one of the holy grails in the field of quantum computing. Whi...
We study the entanglement distance of variational quantum states for two-qubit and multi-qubit systems. These states are constructed using variational...
Multitenancy increases throughput and reduces costs in cloud-based quantum computing, but concurrent job execution introduces security risks through i...
Electro-optic modulators are key components for photonic quantum computing, particularly in fully cryovenic integrated platforms where low loss and co...
Despite rapid recent advances in quantum machine learning, the field is in many ways stuck. Existing approaches can exhibit serious limitations, and w...
Machine learning models can learn from data samples to carry out various tasks efficiently. When data samples are adversarially manipulated, such as b...
The Quantum Lattice Boltzmann Method (QLBM) has emerged as one of the most promising quantum computing approaches for the numerical simulation of prob...
Planar germanium heterostructures hosting hole-spin qubits are among the leading platforms for scalable semiconductor-based quantum computing. Yet, de...
Practical applicability of quantum optimisation on near term devices is constrained by limited qubit counts and hardware noise, which restricts the sc...
Insider Brief PRESS RELEASE — Lawrence Livermore National Laboratory (LLNL) has been selected to lead a project that will receive $4.1 million in fund...
In multi-core quantum computing architectures, waveguide-mediated interconnects are essential for facilitating fast, high-fidelity quantum state trans...
Insider Brief PRESS RELEASE — Qubit Pharmaceuticals, a deeptech company specializing in the discovery of new drug candidates, today announced a strate...
Continuous-variable quantum key distribution (CVQKD) using passive state preparation (PSP) offers low-cost, high-rate secure communication. However, t...
We introduce a quantum algorithm for simulating the dynamics of electrical circuits consisting of resistors, inductors and capacitors (aka RLC circuit...
The pure-loss channel is a fundamental model for describing noise in bosonic quantum platforms. It is characterised by a single parameter, the transmi...
We report the largest trapped-ion hardware demonstration of lattice protein-folding optimization to date, using bias-field digitized counterdiabatic q...
We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor...
Hybrid quantum--classical workflows often execute large ensembles of circuits that differ syntactically but implement identical operations, leading to...
We investigate variational quantum classifiers (VQCs) for land-cover classification from multispectral satellite imagery, adopting a feature-map persp...
Compiling time-evolution operators of the form $U(t)=e^{-iHt}$ into hardware-native gate sequences is a central bottleneck for digital quantum simulat...
Recent advances in quantum computing have enabled the development of quantum processors with hundreds of qubits. However, noise continues to limit the...
Distributed Quantum Computing (DQC) and Quantum Error Correction (QEC) rely on dynamic circuits that include Mid-Circuit Measurements (MCMs) and class...
The decomposition of complex quantum operations into experimentally feasible gate sets has been a central challenge since the early development of qua...
As emerging quantum architectures evolve into heterogeneous networks combining different physical substrates, such as qubits for logic and higher-dime...
The Quantum Approximate Optimization Algorithm (QAOA) follows a single, fixed evolution path, overlooking the potential computational advantage of coh...
We explore what the integrated use of quantum spatial distribution (QSD), or more specifically, superposition of both spin and position states of part...
We find the ground-state energy of the Ising model using the Cascaded Variational Quantum Eigensolver (CVQE) algorithm with the Guided-Sampling Ansatz...
We propose a general method to fully characterize a classical stochastic noise process causing qubit dephasing through repetitive Ramsey interferometr...
In this paper, we resolve an open question in the field of optimization algorithms for training parametrized quantum circuits: Does the popular Rotoso...
Artificial intelligent language-model based coding agents have significantly changed the way we interact with computers in our day-to-day, as it is co...
We study algorithms inspired by quantum annealing that are suited for the NISQ era. First, we analyze approximate quantum annealing (AQA), which emplo...
Bent Boolean functions extremal objects that maximally resist affine approximation are notoriously hard to construct for large numbers of variables. W...
Minor embedding is a required compilation step for quantum annealing, mapping logical problem graphs onto sparse hardware topologies. Despite its cent...
Semiconductor spin qubits are a promising platform for large-scale quantum computing, but have yet to take full advantage of the broad class of quantu...
Noise in contemporary quantum hardware is highly non-uniform across qubits and couplers, giving rise to localized low-noise "islands" within otherwise...
Configuring variational quantum algorithms for combinatorial optimization remains a difficult, expert-driven process requiring coordinated choices ove...
We propose a gate-based quantum algorithm for the prediction step of Bayesian state estimation based on the Fokker-Planck equation on a discretized po...
Insider Brief A quantum computer powerful enough to break the cryptography that secures Bitcoin and Ethereum will eventually be built, and the blockch...
Q-CTRL and IonQ have announced the native integration of Q-CTRL’s Fire Opal software into the IonQ Quantum Cloud. This partnership embeds the Fire Opa...
The National Quantum Algorithm Center (NQAC) at the Illinois Quantum and Microelectronics Park (IQMP) has announced five awards under its Grand Challe...
We describe a numerical many-body technique that is based on both tensor networks and quantum Monte Carlo. The variational ansatz is a tensor network ...
Insider Brief PRESS RELEASE — Today, the National Quantum Algorithm Center (NQAC) at the Illinois Quantum and Microelectronics Park (IQMP) announced f...
Proposed experiments for gravitationally induced entanglement (GIE) typically suppress direct electromagnetic interactions between two massive particl...
Quantum computing may speed up numerical problems involving large matrices that are demanding for classical computers, and active research on this pos...
Hybrid quantum optimization for vehicle routing faces a practical bottleneck: direct QUBO encodings of CVRP quickly exceed near-term qubit and gate bu...
Peaked quantum circuits, whose output distribution is sharply concentrated on a single bitstring, have emerged as a promising candidate for verifiable...
We investigate the limits of quantum error correction (QEC) in neutral-atom processors approaching high-fidelity gates and fast cycle times. We show t...
Execution of quantum algorithms on large-scale quantum computers will require extremely low logical error rates, which necessitates the development of...
The partial oracles framework is a quantum search algorithm that has the potential to exceed the quadratic speedup of Grover's algorithm, up to a theo...
Insider Brief PRESS RELEASE — Zapata Quantum (OTC: ZPTA) (“Zapata”, “Zapata Quantum” or the “Company”), a pioneer in quantum computing application and...
Modular quantum computing architectures require error correction schemes that remain effective in the presence of noisy inter-processor operations. As...
We present a new software package for efficient quantum circuit generation, designed to achieve optimal runtime performance. Despite being in an early...
Insider Brief PRESS RELEASE — Q-CTRL, the global leader in quantum infrastructure software, and IonQ, the world’s leading quantum platform company, to...
Photonic quantum computing provides a promising route toward quantum computation by naturally supporting the measurement-based quantum computation (MB...
We investigate the reduced dynamics of two identical superconducting qubits capacitively coupled through a finite-length transmission line. Starting f...
As quantum hardware scales toward fault tolerant operation, the demand for correct quantum error correction (QEC) circuits far outpaces manual design ...
We develop a path integral representation for the dynamics of quantum systems with a finite-dimensional Hilbert space, formulated entirely within a di...
Sampling problems are promising candidates for demonstrating quantum advantage, and one approach known as quantum-enhanced Markov chain Monte Carlo [L...
Optimization problems become fundamentally challenging as the number of variables increases. Because the volume of the search space grows exponentiall...
Accurate state-of-health (SOH) estimation for lithium-ion batteries remains a challenging problem due to complex electrochemical degradation mechanism...
We adopt a two-dimensional tensor-network (TN) ansatz to simulate variational quantum algorithms on two-dimensional qubit architectures, demonstrating...
Constrained combinatorial optimization problems are frequently reformulated as quadratic unconstrained binary optimization (QUBO) models in order to l...
Quantum Signal Processing (QSP) and Quantum Singular Value Transformation (QSVT) provide an efficient framework for implementing polynomials of block-...
We introduce and empirically validate Landscape Span Compression (LSC), a device-agnostic metric for quantifying how hardware noise distorts the varia...
As quantum computing matures into a practical paradigm, the need for secure and private quantum computation on untrusted hardware becomes increasingly...
Standard quantum error correction (QEC) models typically assume discrete, Markovian noise, obscuring the continuous quantum nature of physical environ...
We simulate a long-range extended Ising model in one dimension using a hybrid quantum algorithm, namely Variational Quantum Eigensolver (VQE). In this...
The limited number of qubits is a major bottleneck in Quantum Approximate Optimization Algorithm (QAOA) for large-scale combinatorial optimization in ...
Superconducting qubits, realized by incorporating Josephson junctions into superconducting circuits, behave as artificial atoms with anharmonic energy...
The long-range transmission of quantum information relies on multiple interfaces between photons, acting as flying qubits, and localized memories, ser...
Quantum coherence plays a pivotal role in quantum algorithms. We study the coherence dynamics of the evolved states in Simon's quantum algorithm based...
Nonlinear spectroscopy is a cornerstone of quantum science, providing unique access to multi-point correlations, quantum coherence, and couplings that...
Quantum technologies promise a radically new way to solve classically intractable computing problems. Superconducting circuits as a platform are at th...
Insider Brief PRESS RELEASE — The use of a quantum-inspired algorithm to calculate the unworkably vast potential properties of quantum materials is an...
Flux-tunable superconducting qubits rely on fast flux control pulses to implement two-qubit entangling quantum gates, a key building block for quantum...
Learning with large-scale datasets and information-critical applications, such as in High Energy Physics (HEP), demands highly complex, large-scale mo...
To study generator design for parameterized unitaries in quantum machine learning (QML), we propose an observable-guided generator selection algorithm...
The impossibility of simultaneously cloning non-orthogonal states lies at the foundations of quantum theory. Even when allowing for approximation erro...
We investigate the generation of quantum states for precision metrology in noisy two-level systems. These states are obtained by optimizing a variatio...
The spin-off company ParityQC has implemented the largest quantum Fourier transform ever reported using an IBM quantum computer, thereby setting a new...
Toward the large-scale, practical realization of quantum computing, quantum error correction is essential. Among various quantum error-correcting code...
Insider Brief PRESS RELEASE — Wellcome Leap (Leap), a U.S. nonprofit founded by the Wellcome Trust to accelerate breakthroughs in human health, today ...
Insider Brief PRESS RELEASE — The European quantum architecture company ParityQC today announced a new record benchmark implementation of the largest ...
ParityQC, a European quantum architecture company, has announced a performance benchmark for the Quantum Fourier Transform (QFT), a foundational algor...
Quantum coherence is a fundamental issue in quantum mechanics and quantum information processing. We explore the coherence dynamics of the evolved sta...
Recently, Dunjko et al.(PRL, 2018) proposed an algorithm for accelerating the solution of 3-satisfiability problems using a small-scale quantum comput...
Quantum coherence plays a central role in Grover's search algorithm. We study the Tsallis relative $α$ entropy of coherence dynamics of the evolved st...
We propose Scalable Quantum Molecular Generation (SQMG), a variational quantum-circuit for sampling molecular graphs using chemical priors on atoms an...
Quantum circuit optimization is a central task in Quantum Computing, as current Noisy Intermediate Scale Quantum devices suffer from error propagation...
Multi-task learning (MTL) improves generalization and data efficiency by jointly learning related tasks through shared representations. In the widely ...
Quantum simulation is a cornerstone application of quantum computing, yet how fundamental quantum resources--entanglement and non-stabilizerness (``ma...
Variational quantum algorithms on bosonic quantum processors are an emerging paradigm for quantum chemistry calculations, exploiting the natural align...
Nature Physics, Published online: 15 April 2026; doi:10.1038/s41567-026-03246-y Quantum simulation of equilibrium many-body systems requires the abili...
The emergence of Cryptographically Relevant Quantum Computers (CRQCs) presents a critical threat to classical cryptographic systems, particularly wide...
Feedback-controlled electromigration (FCE) enables precise regulation of atomic migration by carefully optimizing multiple experimental parameters. Ho...
The quantum kernel method, a promising quantum machine learning algorithm, possesses substantial potential for demonstrating quantum advantage. Althou...
We demonstrate the Parity Architecture on quantum hardware, using the quantum Fourier transform (QFT) as a benchmark. As a result, a record performanc...
Model-independent estimation of the properties of quantum states is a central challenge in quantum technologies, as experimental imperfections, drifts...
We present a quantum optimization framework for the Shipment Selection Problem (SSP) in electric freight logistics, developed jointly by IonQ and Einr...
Geometric frustration, arising from competing interactions that prevent simultaneous energy minimization, presents a fundamental challenge for variati...
Dynamic quantum circuits with mid-circuit measurement and classical feedforward are essential for near-term algorithms such as error mitigation, adapt...
Measurement-based quantum computation (MBQC) is a framework for quantum information processing in which a computational task is carried out through on...
Near-term quantum machine learning (QML) models operate in environments wherein noise is unavoidable, arising from both imperfect classical data acqui...
We present a hardware-validated reference dataset for variational ground-state energy calculations of the hydrogen molecule H\(_2\) on several IBM Qua...
Superconducting quantum computing is advancing toward the thousand- and even million-qubit regime, making wafer-scale fabrication an essential pathway...
We show that quantum computational imaging is advantageous in the setting of low-dose electron microscopy of beam-sensitive specimens. Two qudits plac...
The search for quantum-like wave formulations of the Navier-Stokes (Schrödinger-Navier-Stokes, SNS for short) equations describing classical dissipati...
We present a strategy for the quantum simulation of many-body lattice models with constrained Hilbert spaces. We focus on lattice gauge theories (LGTs...
Quantum error correction (QEC) is essential for scalable quantum computing. However, it requires classical decoders that are fast and accurate enough ...
The integration of large language models (LLMs) into scientific research is accelerating the realization of autonomous ``AI Scientists.'' While recent...
Efficient ground state search is fundamental to advancing combinatorial optimization problems and quantum chemistry. While the Variational Imaginary T...
Variational quantum algorithms (VQAs) have established themselves as a central computational paradigm in the Noisy Intermediate-Scale Quantum (NISQ) e...
Quantum kernel methods (QKMs) have emerged as a prominent framework for supervised quantum machine learning. Unlike variational quantum algorithms, wh...
Deploying quantum machine learning algorithms on near-term quantum hardware requires circuits that respect device-specific gate sets, connectivity con...
Efficiently simulating many-body quantum systems with Coulomb interactions is a fundamental question in quantum physics, quantum chemistry, and quantu...
Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this wor...
In dense neutrino gases, which exist for instance in supernovae, the flavour states of different neutrinos may become entangled with one another. The ...
The Quantum Approximate Optimization Algorithm (QAOA) is a leading framework for quantum combinatorial optimization. The Vehicle Routing Problem (VRP)...
Designing quantum neural networks (QNNs) that are both accurate and deployable on NISQ hardware is challenging. Handcrafted ansatze must balance expre...
The quantum nature of gravity remains experimentally unverified, despite recent proposals to probe it using tabletop experiments such as gravity-media...
We propose a hardware efficient quantum residual neural network which implements residual connections through a deterministic linear combination of id...
Quantum computing simulators form the classical software foundation on which virtually all quantum algorithm research depends. We present Broken Quant...
A particular type of linear optical multiport, the Grover four-port, has previously been shown to couple the spatial symmetry of a photon to its direc...
Quantum operations on pure states can be fully represented by unitary matrices. Variational quantum circuits, also known as quantum neural networks, e...
Assembling genomes from short-read sequencing data remains difficult in repetitive regions, where reference bias and combinatorial complexity limit ex...
While recent advances have established efficient quantum algorithms for preparing Gibbs states of finite-dimensional systems, comparable complexity re...
Due to rising electricity demand, accurate short-term load forecasting is increasingly important for grid stability and efficient energy management, p...
We introduce a hybrid classical-quantum algorithm for simulating a Hamiltonian of the form $H= \sum_{i=1}^K H_i = \sum_{i=1}^K H_{i_1} \otimes H_{i_2}...
Quantum error correction is a crucial technology for fault tolerant quantum computing. On superconducting platforms, hardware defects in large scale q...
Dynamical decoupling is a long-established and effective way to suppress unwanted interactions in qubit systems, enabling advances in fields ranging f...
Consider a rectangular grid of qubits in 2D with single-qubit and nearest-neighbor two-qubit operations subject to local stochastic Pauli noise. At di...
Mid-circuit measurements are one of the biggest practical hurdles in quantum error correction on encoded qubits. Researchers in Innsbruck and Aachen h...
Insider Brief PRESS RELEASE — In August 2024, the National Institute of Standards and Technology finalized the first three post-quantum cryptography s...
Amplitude Amplification offers a provable speedup for search problems, which is leveraged in combinatorial optimization by Grover Adaptive Search (GAS...
We propose a quantum machine learning framework for estimating classical covariance matrices using parameterized quantum circuits within the Pauli-Cor...
When it comes to discriminating between two quantum states, trace distance is one of the well-known metrics used in quantum computation and quantum in...
For quantum algorithms for problems in which the task is to compute an entire field of values, like e.g. computational fluid dynamics (CFD), it is oft...
Quantum phase estimation~(QPE) is central to numerous quantum algorithms, yet its standard implementation demands an $\calO(m^{2})$-gate quantum Fouri...
Insider Brief PRESS RELEASE — With the world’s first scalable, fault-tolerant quantum computer expected to be years away, a group of New Zealand resea...
We introduce the Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Majorana Propagation Eigensolver (ADAPT-VMPE), a quantum-inspired cla...
Insider Brief Quantum hardware is beginning to show measurable gains on real financial problems, with larger qubit systems delivering better portfolio...
Quantum simulation of molecular electronic structure is one of the most promising applications of quantum computing. However, achieving chemically acc...
For strings of letters from a small alphabet, such as DNA sequences, we present a quantum encoding that empirically provides a strong correlation betw...
Quantum computers have the potential to solve certain complex problems in a much more efficient way than classical computers. Nevertheless, current qu...
In the absence of error correction, noisy intermediate-scale quantum devices are operated by training parametrized quantum circuits (PQCs) so as to mi...
Reliable quantum memory is essential for scalable quantum networks and fault-tolerant photonic quantum computing. We present a quantitative analysis o...
Insider Brief PRESS RELEASE — The travelling salesman problem may be the most well-known optimization problem. The problem challenges mathematicians t...
Neutral atom arrays have seen tremendous progress in quantum simulation, quantum metrology, and fault-tolerant quantum computing. However, hardware co...
Guest Post By Baha Jabarin Founder & Product Designer | mimicodesignhouse.com | bahajabarin.com Hybrid quantum-classical workflows, which combine quan...