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Compared to classical computers, quantum computers can solve complex problems in parallel and thus faster, but they are also more prone to errors. ZHAW researchers show how a hybrid approach can be used to exploit the strengths of quantum computers in a targeted manner. Quantum computers not only know the state 0 and 1, but can also represent several states between 0 and 1 by means of so-called qubits - analogous to bits of classical computers - and thus calculate many possible results simultaneously.

A research team from EPFL has developed a novel machine-learning algorithm that can reveal the hidden structure in data recorded from the brain, predicting complex information such as what mice see. Is it possible to reconstruct what someone sees based on brain signals alone? The answer is no, not yet.

A team from the University of Geneva and ID Quantique has developed single-photon detectors with unprecedented performance. These results open new perspectives for quantum cryptography. How can we combat data theft, which is a real issue for society? Quantum physics has the solution. Its theories make it possible to encode information (a qubit) in single particles of light (a photon) and to circulate them in an optical fibre in a highly secure way.

Researchers at Empa, ETH Zurich and the "Politecnico di Milano" are developing a new type of computer component that is more powerful and easier to manufacture than its predecessors. Inspired by the human brain, it is designed to process large amounts of data fast and in an energy-efficient way. In many respects, the human brain is still superior to modern computers.

OpenAI and the recently viral chatbot ChatGPT - in the course of the digital transformation, algorithms, database systems and artificial intelligence are increasingly taking over tasks that were previously performed by humans. What do these changes mean for employees? Peter Kels and Kai Dröge put it in perspective.

Researchers have combined low-power chip design, machine learning algorithms, and soft implantable electrodes to produce a neural interface that can identify and suppress symptoms of various neurological disorders. Mahsa Shoaran of the Integrated Neurotechnologies Laboratory in the School of Engineering collaborated with Stéphanie Lacour in the Laboratory for Soft Bioelectronic Interfaces to develop NeuralTree: a closed-loop neuromodulation system-on-chip that can detect and alleviate disease symptoms.

Researchers have collaborated with those at Harvard and ETH Zurich on a new thin-film circuit that, when connected to a laser beam, produces finely tailorable terahertz-frequency waves. The device opens up a world of potential applications in optics and telecommunications. Researchers led by Cristina Benea-Chelmus in the Laboratory of Hybrid Photonics ( HYLAB ) in EPFL's School of Engineering have taken a big step toward successfully exploiting the so-called terahertz gap, which lies between about 300-30,000 gigahertz (0.3 to 30 THz) on the electromagnetic spectrum.

Researchers have developed a modular system for the simple and inexpensive production of security inks. It is based on polymers and could also be used in solar power plants and screens in the future. Novel fluorescent dyes developed by researchers are relatively simple and inexpensive to produce. The dyes are polymers with a modular structure.

A large-scale analysis of Madagascar's unique biodiversity has just been conducted with the participation of over 50 international organizations. Madagascar is one of the world's biodiversity hotspots, with 82% of its plant species and 90% of its vertebrates found nowhere else on Earth. The results of the study, which rely on AI-based tools developed by Daniele Silvestro of the Swiss Institute of Bioinformatics and his team at the University of Fribourg, were published in two papers in the journal Science.

Researchers from EPFL and ETH Zurich, working together with the International Committee of the Red Cross (ICRC) and Bin Khalifa Unversity (Qatar), have developed a program that can generate population density estimates with unparalleled precision, and only needs a rough estimate at the regional level to learn.

A team of scientists at EPFL have built a new neural network system that can help understand how animals adapt their movement to changes in their own body and to create more powerful artificial intelligence systems. Deep learning has been fueled by artificial neural networks, which stack simple computational elements on top of each other, to create powerful learning systems.

Borrowing from methods used to produce optical fibers, researchers from EPFL and Imperial College have created fiber-based soft robots with advanced motion control that integrate other functionalities, such as electric and optical sensing and targeted delivery of fluids. Over the past decades, catheter-based surgery has transformed medicine, giving doctors a minimally invasive way to do anything from placing stents and targeting tumors to extracting tissue samples and delivering contrast agents for medical imaging.

Chemical engineers at EPFL have developed a machine-learning model that can accurately predict the heat capacity of the versatile metal-organic framework materials. The work shows that the overall energy costs of carbon-capture processes could be much lower than expected. Metal-organic frameworks (MOFs) are a class of materials that contain nano-sized pores.

With energy prices soaring, heating costs will also inevitably rise in the coming winter. In order to mitigate this, solutions for operating buildings more efficiently are needed. The Empa spin-off viboo has developed an algorithm that makes it possible to operate even older buildings with around 25 percent less energy - while user comfort remains the same or even improves.

An innovative new collaboration between EPFL's HexHive Laboratory and Oracle has developed automated, far-reaching technology in the ongoing battle between IT security managers and attackers, hoping to find bugs before the hackers do. On the 9th of December 2021 the world of IT security went into a state of shock.

Researchers have discovered a serious security vulnerability in computer hardware. The vulnerability, called "Retbleed," affects microprocessors from market leaders Intel and AMD. All commercially available operating systems worldwide that use these processors are affected. When computers execute special calculation steps to compute faster, they leave traces that hackers could abuse.

Researchers from ETH Zurich, the University of Zurich and Empa have developed a new material for an electronic component that can be used in a wider range of applications than its predecessors. Such components will help create electronic circuits that emulate the human brain and that are more efficient at performing machine-learning tasks.

Researchers from ETH Zurich, Empa and the University of Zurich have developed a new material for an electronic component that can be used in a wider range of applications than its predecessors. Such components will help create electronic circuits that emulate the human brain and that are more efficient than conventional computers at performing machine-learning tasks.

Scientists have developed a digital model of the fruit fly, Drosophila melanogaster, which realistically simulates the movements of the animal. The twin is a big step towards reverse engineering the neuromechanical control of animal behavior, and developing bioinspired robots. "We used two kinds of data to build NeuroMechFly," says Professor Pavan Ramdya at EPFL's School of Life Sciences.

Countless chemical substances, including fertilisers and pesticides but also pharmaceutical substances and industrial products, leak into groundwater, lakes and rivers. "We want to know what the impact of these chemicals is on aquatic species, and whether they are toxic or not," says Marco Baity-Jesi, Head of the Eawag Data Science Group.