100 curated articles
Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing. However, scaling to useful fault-tolerant processors will likely generate thermal loads that exceed the cooling power available at millikelvin temperatures. Ra...
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...
Author(s): Casper Gyurik, Alexander Schmidhuber, Robbie King, Vedran Dunjko, and Ryu Hayakawa A quantum algorithm achieving exponential speedup for a ...
AWS and QuEra will bring the first fault-tolerant quantum computers to the cloud, enabling scientifically relevant applications starting in 2028. Sinc...
This post was contributed to by Zia Mohammad, Scott Smart, Yuvraj Mohan, Mike Piech, and Rebecca Malamud Figure 1: A Rigetti quantum processing unit (...
Two recent papers suggest that quantum computers may crack modern cryptography sooner than expected The post New findings shorten the road to cryptogr...