The Future of Quantum Computing

Breaking news, scored company profiles, and ecosystem intelligence across the global quantum sector — plus the deepest coverage of India's National Quantum Mission.

World’s First Superconducting Quantum Heat Engine Could Help Unlock Massive Quantum Computers
Featured Story

World’s First Superconducting Quantum Heat Engine Could Help Unlock Massive Quantum Computers

A newly developed superconducting quantum heat engine could deepen our understanding of thermodynamics while helping advance technologies needed for quantum computers with very large numbers of qubits.Scientists are getting a clearer picture of how thermodynamics behaves in the quantum world, and that progress could benefit both quantum technology and our understanding of familiar thermodynamic principles. Researchers at Aalto University have now taken an important step by demonstrating the first cyclic quantum heat engine built inside a superconducting circuit.The experiment connects two areas of physics that normally describe very different scales. Quantum mechanics explains the behavior of matter at extremely small scales, even below the size of atoms, while thermodynamics describes how heat and energy behave in much larger systems, from collections of molecules to the universe itself. Bringing the two together raises a fundamental question: what happens to familiar thermodynamic processes when quantum effects such as tunneling, entanglement, and superposition enter the picture?A Heat Engine Built for the Quantum WorldConventional heat engines turn heat into useful work. James Watt's steam engine is one famous example, but the same basic concept remains central to modern transportation and electricity production, powering cars, ships, planes and many power plants.The researchers have now created the world's first superconducting quantum heat engine. The extremely small device combines a transmon qubit, a resonator and a quantum refrigerator.Operating under ultracold quantum conditions, the engine was able to use the tiny amount of available heat to repeatedly produce positive work. Achieving this kind of cyclic operation has been an important objective for researchers working on quantum heat engines. The result provides a proof of concept for superconducting heat engines that could eventually contribute to improved quantum computing technology.The study, led by A

Aug 15, 2026

Featured Stories

View All Stories
Shaanxi Normal University Maps Gate Design to Evolution-Level Controlquantum-computing

Shaanxi Normal University Maps Gate Design to Evolution-Level Control

Shaanxi Normal University and Xi’an University of Posts and Telecommunications researchers are shifting the focus of quantum gate design from optimizing pulse amplitudes to learning the entire process of quantum evolution, utilizing a method called physics-informed neural networks. The work represents a move beyond simply finding a control solution to understanding the underlying structure of how that control is achieved. Rather than pre-defining control pulse shapes or durations, the team’s approach allows the artificial intelligence to independently arrive at physically expected results. For rotation gates, the optimized evolutions recover the physical organization expected for bounded single-qubit control, with no prescribed pulse ansatz or duration scan. This method not only synthesizes gates but also makes optimized quantum controls physically readable, diagnosable, and locally refinable, identifying localized bottlenecks in maintaining the geometric condition and using this diagnosis as feedback. Researchers at Shaanxi Normal University and Xi’an University of Posts and Telecommunications are developing a new approach to quantum gate design, moving beyond traditional pulse optimization to directly learn quantum evolution. This represents a fundamental shift from controlling how to control to controlling the process itself. This work, detailed in recent findings, utilizes physics-informed neural networks (PINNs) to represent the entire evolution of a single-qubit gate, simultaneously learning the control fields, Bloch-state trajectories, and total duration under the governing Bloch equation. Unlike conventional methods that treat pulse parameters as the primary optimization target, this approach views the gate as a unified dynamical object, where control, evolution, and time are intrinsically linked. Crucially, the representation doesn’t merely synthesize gates, but also enables a level of diagnostic control previously unavailable. When applied to geometric gat

Quantum ZeitgeistLoading...0
Quantum Engines Face Higher Costs for Greater Measurement Precisionquantum-computing

Quantum Engines Face Higher Costs for Greater Measurement Precision

Jonas Berx of Niels Bohr International Academy, Niels Bohr Institute, University of Copenhagen, and colleagues at Chalmers University of Technology have demonstrated a quantum engine where the work it produces is directly linked to the precision of its measurements. The research details how extracting work conditionally, based on measurement outcomes of a two-level system, presents a trade-off between extractable work and its fluctuations. Reducing fluctuations in work output, the team found, requires greater information consumption, more engine cycles, longer operation time, and ultimately, reduced average work output. In the limit of highly accurate measurement, the engine’s work statistics reduce to those of a qubit interacting with a thermal bath; this suggests fundamental connections between complex quantum engines and basic quantum systems. Using a genetic algorithm for multi-objective optimization, they identified Pareto fronts representing the best possible trade-offs between extractable work and its fluctuations. The results provide a compact description of the trade-offs between work, its fluctuations, and thermodynamic costs in quantum information engines. Pareto-Optimal Work Extraction in Quantum Engines Maximizing work output from a quantum engine invariably introduces fluctuations, but a new analysis reveals a precise trade-off between performance and reliability. Researchers have demonstrated that diminishing these fluctuations demands increased thermodynamic costs, a finding with implications for the design of increasingly practical quantum-scale devices. The work, appearing this month, moves beyond simply maximizing average energy extraction to consider the broader implications of consistent, dependable output. Using a genetic algorithm for multi-objective optimization, they identified Pareto fronts representing the best possible trade-offs between extractable work and its fluctuations. This approach, widely used in engineering and economics, is onl

Quantum ZeitgeistLoading...0

From Quantum Authors

View Guest Articles

Trending Stories

View All Trending
Quantum News

Get the Quantum News Newsletter

Weekly insights • No spam • Unsubscribe anytime

India National Quantum Mission

Explore India's ₹6,003 Crore quantum initiative: 4 thematic hubs, leading startups, and the latest developments in India's quantum ecosystem

View All India NQM Content