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个人简介
During his research career, Gu has established a string of novel connections between scientific concepts that were previously unrelated. Notable contributions include a proof – using the methods of theoretical computer science – that not all properties of a macroscopic system can be determined from microscopic laws (see Nature 459, 332-334) and demonstrate that quantum mechanics may change what systems are considered complex (Nat. Comm 3,76). In addition, Gu jointly demonstrated that the simplest solution to a computational problem can be thought as free fall in some curved space, and discovered that different quantum phases may have different computational power.
One of the most remarkable facts about the universe is that it can be simulated on a computer. No matter what systems we study, whether it is the dynamics of planets or that of fluids, the rise of fall of tides or stock markets, they all can be simulated by a computer. This fact fascinates me.
After all, a computer is typically built out of silicon; it runs via the electro-magnetic force. What a priori reason would it allow us to understand the motion of planets governed by gravity, fundamental particles govern by the strong and weak force? This universality is, when you think about, rather remarkable. Somehow, everything we know around us, can be reduced to the processing of information.
My research interests are motivated by this remarkable observation. Can we find interdisciplinary laws that span multiple disciplines through the understanding of how nature fundamentally processes information? Some current directions:
On outset, Quantum and complexity science appears to be very different. The former details with objects at the atomic scale – atoms, electrons and photons. The latter, on the other hand, is typically associated with macroscopic systems is many interacting components – the weather, traffic, stock markets.
Yet the two science, in fact, an intimately linked; both are bring transformed by the study of information. In quantum science, new information theoretic techniques have allowed the `second quantum revolution’; heralding exciting new quantum technologies such as quantum cryptography and quantum computation. Meanwhile, in complexity science, researchers’ new ways of understanding just how massive systems interact with each other by seeing how they transform and process bits of data.
My interest is to unite these two fields – by forging new connections. Can quantum computation lead to new ways of understanding complex systems? Can the use of methods of complexity science help us understand how quantum computer’s get their power and bring forth new quantum technologies?
One of the most remarkable facts about the universe is that it can be simulated on a computer. No matter what systems we study, whether it is the dynamics of planets or that of fluids, the rise of fall of tides or stock markets, they all can be simulated by a computer. This fact fascinates me.
After all, a computer is typically built out of silicon; it runs via the electro-magnetic force. What a priori reason would it allow us to understand the motion of planets governed by gravity, fundamental particles govern by the strong and weak force? This universality is, when you think about, rather remarkable. Somehow, everything we know around us, can be reduced to the processing of information.
My research interests are motivated by this remarkable observation. Can we find interdisciplinary laws that span multiple disciplines through the understanding of how nature fundamentally processes information? Some current directions:
On outset, Quantum and complexity science appears to be very different. The former details with objects at the atomic scale – atoms, electrons and photons. The latter, on the other hand, is typically associated with macroscopic systems is many interacting components – the weather, traffic, stock markets.
Yet the two science, in fact, an intimately linked; both are bring transformed by the study of information. In quantum science, new information theoretic techniques have allowed the `second quantum revolution’; heralding exciting new quantum technologies such as quantum cryptography and quantum computation. Meanwhile, in complexity science, researchers’ new ways of understanding just how massive systems interact with each other by seeing how they transform and process bits of data.
My interest is to unite these two fields – by forging new connections. Can quantum computation lead to new ways of understanding complex systems? Can the use of methods of complexity science help us understand how quantum computer’s get their power and bring forth new quantum technologies?
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PRX Quantumno. 3 (2024): 030303
arxiv(2024)
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PHYSICAL REVIEW Ano. 2 (2024)
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