A University of Arizona team advances low-density parity check codes for quantum computers, enabling fault-tolerant and ultra-fast computation. The development is crucial for solving complex equations and analyzing phenomena that classical computers can't handle.
Researchers have developed a quantum algorithm that can diagnose noise in large quantum systems, enabling the creation of more reliable and scalable quantum computers. The algorithm was tested on a 14-qubit machine and discovered correlations not previously detected.
The ACM SIGCOMM conference emphasizes the importance of communications technologies in maintaining daily life. The virtual event showcases research papers on various topics, including programmable switches and video applications. Keynote speakers are recognized for their contributions to data network architectures, and the conference a...
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Researchers at Skoltech developed a quantum enhanced machine learning approach that uses quantum states as data, overcoming the 'data-readin problem'. This allows for faster calculations and better performance than classical machines in certain applications.
Researchers at UVA have developed an algorithm to classify genomic data using quantum computers, potentially revolutionizing the field of genetic research. The new technology could analyze vast amounts of genetic data exponentially faster than conventional computers.
A new quantum classifier introduces a tailored quantum kernel, outperforming AI technology and enhancing classification tasks with small datasets. The method exploits the quantum advantage in finding non-linear features, leading to significant improvements.
A study has described how teleportation can be used to create a high-tech jamming session between a human musician and a quantum computer. The result is a unique performance piece combining live human and computer-generated sounds.
Researchers have developed a new SSO algorithm that prevents holistic information exchange between users and service providers, ensuring better privacy. The algorithm uses encrypted messages and secure authentication to protect sensitive personal data.
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Researchers adapt robotics techniques to efficiently assess quantum device performance, stabilizing the emerging technology. This innovative approach outperforms simplistic characterisation in complex simulated environments.
Silq allows programmers to utilize quantum computers' potential better than existing languages, with more compact and faster code. The language also automatically identifies and erases unnecessary values through uncomputation, improving the reliability of quantum calculations.
Researchers developed an advanced quantum algorithm for measuring physical quantities using simple optical tools, exceeding the shot noise limit and achieving Heisenberg-limited sensitivity. This breakthrough enables affordable and effective platforms for moderate-scale quantum measurements and computations.
Cynthia Dwork has received the Knuth Prize for her groundbreaking work on cryptography in network environments, privacy, and foundational contributions to theoretical computer science. Her research transformed several fields, including distributed systems, data privacy, and fairness in algorithmic decision making.
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Researchers have developed TurboRVB, a first-principles quantum Monte Carlo package that overcomes drawbacks of density functional theory and wavefunction-based calculations. The code features resonating valence bond-type wave functions, state-of-the-art optimization algorithms, and lattice-regularized diffusion Monte Carlo method.
A team of Skoltech scientists discovered reachability deficits in the widely adopted QAOA algorithm, limiting its ability to solve certain problems. The study found that QAOA's performance depends on the problem density, with high-density instances having optimal solutions that cannot be approximated with guaranteed success.
Scientists at Tokyo University of Science develop a new quantum algorithm to analyze complex networks, finding that fractal properties play a crucial role in determining optimal computational time. The researchers propose a new scaling hypothesis to gain more insight into different fractal geometries.
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Researchers highlight successes and challenges of quantum computing in the NISQ era, a period where quantum computers approach evidence of quantum supremacy. Key findings include the development of new strategies to reduce measurement errors and the demonstration of programmability on quantum computers.
Researchers at Aarhus University used AlphaZero to control a quantum system, demonstrating its applicability to three different problems. The algorithm learned to exploit an underlying symmetry of the problem, surprising the team with its ability.
A team of researchers from MIT has developed an algorithm to solve hard combinatorial problems using optical machines. This breakthrough has the potential to revolutionize fields such as biology, drug discovery, and routing/scheduling by leveraging the advantages of optical hardware integrated into silicon photonics.
Researchers have created an algorithm to simulate electromagnetic wave interactions with materials, reducing simulation time from months to hours. This breakthrough could lead to more efficient and accurate equipment in fields like biology, astronomy, and telecommunications.
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Researchers at Universitat Autonoma de Barcelona developed an optimal procedure to identify clusters of identically prepared quantum systems, solving the challenge of sorting quantum data. The new protocol outperforms classical strategies, particularly for large dimensional data.
Researchers at University of Michigan discovered a new way to calculate interaction between metals and alloying materials, enabling faster search for materials with high hardness and resistance to cracking. This breakthrough could accelerate development of better alloys for turbine engines and nuclear reactors.
The Department of Energy has awarded Oak Ridge National Laboratory over $11 million to advance quantum technologies, including computing and fiber optics. Researchers will work on projects aimed at accelerating progress in quantum computing and developing wide-area quantum networks.
Scientists have shown that quantum computers have two degrees of freedom for each bit, enabling faster calculations. A simulation tool called Quantum Simulation Logic has been developed to simulate quantum computer properties in a classical computer.
A Berkeley Lab-led team used quantum annealing to solve a tough math problem that stumps even the world's most powerful supercomputers. The algorithm can evaluate multiple variables simultaneously and return the correct solution, potentially revolutionizing fields like systems engineering and operations research.
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Los Alamos National Laboratory scientists have developed a new quantum computing algorithm to investigate the quantum-to-classical transition in systems like biological proteins. The algorithm allows for the search for classicality in quantum systems, providing insights into how quantum mechanics applies to large-scale objects.
A team of Virginia Tech researchers has advanced quantum simulation by devising an algorithm that can more efficiently calculate the properties of molecules on a noisy quantum computer. The breakthrough enables simulating molecular properties, which can lead to advances in materials improvement and drug discovery.
Scientists have developed a quantum algorithm that can process large sets of data faster and more accurately than standard methods. The Kravchuk transform, a quantum counterpart of the Fast Fourier Transform (FFT), enables efficient processing of digital images, sound, and radio signals.
Hybrid algorithms employ classical and quantum capabilities to address limitations of near-term quantum hardware. The approach can tackle optimization problems like graph partitioning and clustering, enabling researchers to use existing quantum hardware for practical applications.
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Researchers at Osaka City University develop a quantum algorithm to determine spin quantum numbers on quantum computers, enabling accurate wave function calculations. This breakthrough solves complex issues in chemistry and physics, accelerating the development of practical quantum computers.
Researchers from Nanyang Technological University and Griffith University have developed a prototype quantum device that can examine all possible futures by placing them in a quantum superposition. This allows for the simulation of statistical futures and could enable more efficient learning in artificial intelligence algorithms.
Researchers at Tohoku University developed an algorithm to improve the D-Wave quantum annealer's ability to solve complex combinatorial optimization problems. The new algorithm allows for larger subproblems, leading to more optimal solutions efficiently.
D-Wave's quantum annealing algorithm and quantum computer have been shown to break RSA codes with unprecedented efficiency, outperforming universal quantum computers like Shor's algorithm. This breakthrough highlights the potential of D-Wave for cryptanalysis and code-cracking.
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An international team of scientists successfully reversed the flow of time on IBM's quantum computer, simulating a particle's scattering and returning it to its initial state. The breakthrough could lead to more efficient quantum computer operation and improved error correction methods.
A study published in Physical Review Letters demonstrates that algorithms based on deep neural networks can better understand quantum physics phenomena. Researchers found a way to harness AI to enhance understanding of quantum behavior, potentially revolutionizing various aspects of life.
Sandia National Laboratories has launched four new projects to advance quantum computing, including a 'testbed' for industrial and academic researchers. The projects focus on creating accessible components, high-level algorithms and tools to measure quantum hardware performance.
Researchers from Osaka City University have developed a novel quantum algorithm to perform full configuration interaction calculations suitable for predicting chemical reactions, overcoming the exponential/combinatorial explosion of traditional methods. This breakthrough enables practical applications of quantum chemistry on quantum co...
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Researchers from Osaka City University have developed a quantum algorithm capable of performing full configuration interaction calculations for any open shell molecules in polynomial time, overcoming the exponential explosion challenge. This breakthrough enables practical applications of quantum computers in chemistry and physics.
Researchers at Kazan Federal University developed cryptographic algorithms for quantum networks, which can facilitate fast and secure information transfer. The algorithms, known as quantum hash functions, can protect against mistakes and be used for authentication in various areas.
Researchers at UPV/EHU designed a model of quantum artificial life that encodes quantum behaviors similar to living systems. The model, executed on an IBM ibmqx4 cloud quantum computer, simulates birth, self-replication, interaction between individuals and the environment.
Researchers developed a remote gaming interface that allowed external experts and citizen scientists to optimize a quantum gas experiment in real-time. The team found that collective search behavior of humans balances innovative attempts and refines existing solutions, making human problem-solving unique.
Researchers at UC Berkeley have developed a practical proposal known as random circuit sampling (RCS) to prove quantum supremacy in quantum computers. This technique uses complex mathematical constructs to demonstrate the 'quantum accent' of a device, making it difficult for classical computers to replicate.
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Scientists have developed a quantum circuit that demonstrates the advantage of quantum computers over classical systems. The new design exploits quantum physics' non-locality to solve complex problems efficiently. This breakthrough brings us closer to realizing near-term experimental realizations of quantum algorithms.
Johan Torkel Håstad of KTH Royal Institute of Technology is awarded the 2018 Donald E. Knuth Prize for his significant contributions to computer science, including optimization and cryptography. The prize recognizes his transformative techniques that have influenced subsequent work in these areas.
A new algorithm developed by University of Illinois researchers enables condensed matter physicists to find interesting properties in materials. The algorithm starts with the desired type of physics and works backward to generate Hamiltonians, which can predict or explain material behaviors.
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Researchers have developed an algorithm that can discover and optimize thermoelectric materials in a matter of months, rather than years. The new method simplifies computational approaches for electron-phonon scattering, speeding up the process by about 10,000 times and reducing development time.
Yale researchers have achieved a major milestone in quantum computing by transmitting quantum data between two separate points using a new 'pitch-and-catch' technology. This innovation allows qubits to be interfaced with each other, enabling more complex algorithms and potentially faster computation speeds than classical computers.
Researchers will co-design hardware and software to realize quantum computing's potential more rapidly, focusing on efficient algorithms and tools for programming and education. The collaboration aims to create a community of academic and industry partners to drive progress in the field.
Researchers have developed a quantum linear system algorithm that enables faster analysis of large data sets, outperforming classical computers. The new algorithm has the potential to revolutionize fields like commodities pricing, social networks, and chemical structures.
Scientists at KIT successfully implemented Grover's quantum algorithm using a molecular magnet to quickly find specific elements in unsorted data. The technology quadratically accelerates search and can be integrated into current electronic devices.
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Two ORNL-led research teams will assess the feasibility of quantum architectures in addressing big science problems and develop algorithms to harness massive power predicted by quantum computing systems. Researchers aim to create quantum computers capable of simulating phenomena at unprecedented scales and speeds.
Researchers found that super-powerful quantum computers must be even more powerful than previously thought to outperform ordinary PCs. The team simulated boson sampling for 20-50 photons on laptops and servers, pushing the boundary of what is possible.
Researchers found that certain physical phenomena, such as the thermal Hall conductance, cannot be simulated efficiently due to a negative sign or complex quantities involved in quantum Monte-Carlo methods. This limits the scalability of large-scale quantum simulations and provides reassurance for theoretical physicists.
Quantum computers threaten to destroy current internet security methods as they can break RSA and ECC systems in days or hours. Researchers like Tanja Lange are working on alternative systems, including a $3.9 million EU-funded research consortium.
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Researchers at Oak Ridge National Laboratory have developed a method to produce controlled, deterministic photons that can be used in novel cryptographic technologies. This innovation aims to improve the speed and security of quantum key encryption when sharing information over machine-to-machine networks.
The journal has achieved a high impact factor of 9.111, demonstrating its influence on the scientific community. UNSW is proud to be a leader in the global sharing of knowledge in this rapidly evolving field.
Researchers from Tsinghua University and Southern University of Science and Technology successfully experimentally studied the Forrelation problem in a 3-qubit nuclear magnetic resonance quantum information processor. The study aimed to find the largest possible separation between quantum and classical query complexities, with potentia...
Scientists have created stable qubits using supramolecular chemistry, enabling the connection of individual qubits into structures called two-qubit gates. This approach has potential for creating multi-qubit gates and advancing quantum computing.
Researchers used a novel quantum Monte Carlo technique to study the Rabi model's accuracy at the quantum scale. They found dramatic consequences for strongly coupled light-atom systems, emphasizing the need to account for non-conserved excitations.
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The new module combines proven techniques with advances in hardware and software to run arbitrary algorithms on five qubits. It enables the flexibility to test the module on a variety of problems, bringing practical quantum computing closer to reality.
Scientists at the University of Bristol have developed a new method to simulate a 'quantum walk' on a primitive quantum computer, which they claim can solve problems that classical computers cannot. The study suggests that these smaller quantum processors could outperform classical computing for specific tasks, such as 'Boson Sampling'.