Lifeboat Foundation

Daniel Dennett when Hal kills whose to blame computer ethics.

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The number of quantum computing use cases is growing. Using a combination of quantum computing technologies might propel companies looking to stay ahead of the curve in their respective industries.

The dynamic characteristics of the inverters have been simulated by varying the inverter output (load) capacitance (C_OUT), connected to the inverter output across a 1000 nm long interconnect (assumed for simulations of the NM circuit, described in “NM circuit” subsection), from 1 aF to 1 fF. By evaluating the delay \(({t}_{{{{{{\rm{p}}}}}}})\) of the input-to-outpution, and the instantaneous current drawn from the supply during thision, the average power dissipation, and the energy-delay-product (EDP), is evaluated for both the 2D-TFET and the FinFET implementations. The higher delay of the 2D-TFET (due to its lower ON-current) translates to higher EDP, and the EDP metrics get worse as the load capacitance is further increased. In fact, as will be shown later, the main advantages of TFETs are in implementations of sparse switching circuits where its much lower OFF-current and small SS help in lowering the static power dissipation, thereby improving the overall performance.

Figure 2c shows an 11-stage ring oscillator, implemented considering both interconnect and device parasitics, and designed with minimum sized 2D-TFET and FinFET inverters. Figure 2 d, e compares the transient characteristics of the FinFET and the 2D-TFET ring oscillators, from which the frequency of oscillation is extracted to be 10 GHz and 57 MHz, respectively, corresponding to single-stage delays of 10 ps and 1.6 ns. The delay of the 2D-TFET ring oscillator is larger due to its lower ON-current. The effect of the enhanced Miller capacitance in creating large overshoots and undershoots of the output voltage in TFETs is also observed in Fig. 2e.

Static random-access memory (SRAMs), which occupy up to 70% of the processor area are the main memory elements in designing CPU cache memory offering fast memory access and can be used for synapse weight retention in a designed NM system comprising of several neurons. However, this large prevalence of SRAMs also results in a large power consumption. In fact, SRAM data access in Intel’s Loihi⁵ has been estimated to be more energy intensive than each neuronal spike, necessitating the development of low-power SRAM implementations. Although SRAM design with 2D-TFETs can improve the energy-efficiency, the standard SRAM design utilizes two access transistors for operation, which require bidirectional current flow, and are therefore, ill-suited for implementation with unidirectional-TFETs. This necessitates the development of a modified SRAM design, which either uses a pass transistor network of TFETs, or solitary 2D-FETs, for implementing the function of the access transistors (Fig. 2f–l).

Researchers Kazuaki Takasan and Kyogo Kawaguchi of the University of Tokyo with Kyosuke Adachi of RIKEN, Japan, have demonstrated that ferromagnetism, an ordered state of atoms, can be induced by increasing particle motility and that repulsive forces between atoms are sufficient to maintain it.

The discovery not only extends the concept of active matter to quantum systems but also contributes to the development of novel technologies that rely on the magnetic properties of particles, such as magnetic memory and quantum computing. The findings were published in the journal Physical Review Research.

Flocking birds, swarming bacteria, cellular flows. These are all examples of active matter, a state in which individual agents, such as birds, bacteria, or cells, self-organize. The agents change from a disordered to an ordered state in what is called a “phase transition.” As a result, they move together in an organized fashion without an external controller.

Abstract. In recent years, brain research has indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modelling at multiple scales—from molecules to the whole brain. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain combines high-quality research, data integration across multiple scales, a new culture of multidisciplinary large-scale collaboration, and translation into applications. As pioneered in Europe’s Human Brain Project (HBP), a systematic approach will be essential for meeting the coming decade’s pressing medical and technological challenges.

Scientists have introduced a form of quantum entanglement known as frequency-domain photon number-path entanglement. This advance in quantum physics involves an innovative tool called a frequency beam splitter, which has the unique ability to alter the frequency of individual photons with a 50% success rate.

For years, the scientific community has delved into spatial-domain photon number-path entanglement, a key player in the realms of quantum metrology and information science.

This concept involves photons arranged in a special pattern, known as NOON states, where they’re either all in one pathway or another, enabling applications like super-resolution imaging that surpasses traditional limits, the enhancement of quantum sensors, and the development of quantum computing algorithms designed for tasks requiring exceptional phase sensitivity.

An international collaboration of researchers, led by Philip Walther at University of Vienna, have achieved a significant breakthrough in quantum technology, with the successful demonstration of quantum interference among several single photons using a novel resource-efficient platform. The work published in the prestigious journal Science Advances represents a notable advancement in optical quantum computing that paves the way for more scalable quantum technologies.

Interference among photons, a fundamental phenomenon in quantum optics, serves as a cornerstone of optical quantum computing. It involves harnessing the properties of light, such as its wave-particle duality, to induce interference patterns, enabling the encoding and processing of quantum information.

In traditional multi-photon experiments, spatial encoding is commonly employed, wherein photons are manipulated in different spatial paths to induce interference. These experiments require intricate setups with numerous components, making them resource-intensive and challenging to scale.

In a future with more ‘mind reading,’ thanks to computer-brain interfaces, we may need to rethink freedom of thought.

Scaling up qubit counts in quantum computers is at the core of achieving quantum supremacy.

Among the troublesome hurdles of this scaling-up race is refining how qubits are measured. Devices called parametric amplifiers are traditionally used to do these measurements. But as the name suggests, the device amplifies weak signals picked up from the qubits to conduct the readout, which causes unwanted noise and can lead to decoherence of the qubits if not protected by additional large components. More importantly, the bulky size of the amplification chain becomes technically challenging to work around as qubit counts increase in size-limited refrigerators.

Cue the Aalto University research group Quantum Computing and Devices (QCD). They have a hefty track record of showing how thermal bolometers can be used as ultrasensitive detectors, and they just demonstrated in an April 10 Nature Electronics paper that bolometer measurements can be accurate enough for single-shot qubit readout.

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