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Pengyu Liu

Publications and source records attributed to Pengyu Liu.

At least 37 records · Page 2Linked to original sources

ConiQ: Enabling Concatenated Quantum Error Correction on Neutral Atom Arrays

Recent progress on concatenated codes, especially many-hypercube codes, achieves unprecedented space efficiency. Yet two critical challenges persist in practice. First, these codes lack efficient implementations of addressable logical gates. Second, the required high degree of parallelism and long-range interactions pose significant challenges for current hardware platforms. In this paper, we propose an efficient compilation approach for concatenated codes, specifically many-hypercube codes, targeted at neutral atom arrays, which provide the necessary parallelism and long-range interactions. Our approach builds on two key innovations. First, we introduce Automorphism-assisted Hierarchical Addressing (AHA) logical CNOT gates that significantly reduce spacetime overhead compared to conventional distillation-based methods. Second, we develop Virtual Atom Intermediate Representation (VAIR) that enables level-wise optimization and legalization. We implement these innovations in ConiQ, a hardware-aware quantum compiler designed to compile fault-tolerant quantum circuits for neutral atom arrays using many-hypercube codes. Our evaluation demonstrates that ConiQ achieves up to 2000x reduction in spacetime overhead and up to 10^6x reduction in compilation time compared to state-of-the-art compilers, with our AHA gates providing an additional overhead reduction of up to 20x. These results establish concatenated codes as a promising approach for fault-tolerant quantum computing in the near future.

cs.AR↗

POPQC: Parallel Optimization for Quantum Circuits (Extended Version)

Optimization of quantum programs or circuits is a fundamental problem in quantum computing and remains a major challenge. State-of-the-art quantum circuit optimizers rely on heuristics and typically require superlinear, and even exponential, time. Recent work proposed a new approach that pursues a weaker form of optimality called local optimality. Parameterized by a natural number $Ω$, local optimality insists that each and every $Ω$-segment of the circuit is optimal with respect to an external optimizer, called the oracle. Local optimization can be performed using only a linear number of calls to the oracle but still incurs quadratic computational overheads in addition to oracle calls. Perhaps most importantly, the algorithm is sequential. In this paper, we present a parallel algorithm for local optimization of quantum circuits. To ensure efficiency, the algorithm operates by keeping a set of fingers into the circuit and maintains the invariant that a $Ω$-deep circuit needs to be optimized only if it contains a finger. Operating in rounds, the algorithm selects a set of fingers, optimizes in parallel the segments containing the fingers, and updates the finger set to ensure the invariant. For constant $Ω$, we prove that the algorithm requires $O(n\lg{n})$ work and $O(r\lg{n})$ span, where $n$ is the circuit size and $r$ is the number of rounds. We prove that the optimized circuit returned by the algorithm is locally optimal in the sense that any $Ω$-segment of the circuit is optimal with respect to the oracle.

cs.DC↗

A planetary-mass candidate imaged in the Young Suns Exoplanet Survey

Directly imaged exoplanets in wide orbits challenge current gas giant formation theories. They need to form quickly and acquire enough material before the disk dissipates, which cannot be accommodated by in-situ formation by core accretion. We search for wide separation ($>$ 100 au) planetary-mass companions with the Young Suns Exoplanet Survey (YSES). Here, we present a planetary-mass candidate companion discovered in the survey. We conducted follow-up observations of the candidate system after the first epoch observations and obtained six epochs of observations for this system between 2018 and 2024, and integral field spectroscopy of the stellar component. We report the detection of a candidate companion with H=22.04 $\pm$ 0.13 mag at a projected separation of 730 $\pm$ 10 au away from the primary star. High angular resolution imaging observations of the central star show it is a visual binary. Acceleration data, orbital fitting, spectral energy distribution fitting and radial velocity differences all suggest that there is at least one more unresolved low-mass stellar companion in this system. The planetary-mass candidate shows a significant proper motion comparable to that of the primary star. We estimate an age of 19-28 Myr for the primary star. We cannot confirm the companionship of the candidate due to the unknown barycentre of the stars. Long-term imaging and radial velocity monitoring of the central stars, along with spectroscopy of the candidate companion, are key to resolving the nature of this system. If confirmed, the candidate companion would have a mass of 3-5 Mj estimated with the ATMO evolutionary model. It would be another cold low-mass planet imaged similar to 51 Eri b and AF Lep b. Its extremely wide separation from the host star would challenge the formation theory of gas giant exoplanets.

astro-ph.EP↗

The JWST weather report from the nearest brown dwarfs II: Consistent variability mechanisms over 7 months revealed by 1-14 $μ$m NIRSpec + MIRI monitoring of WISE 1049AB

We present a new epoch of JWST spectroscopic variability monitoring of the benchmark binary brown dwarf WISE 1049AB, the closest, brightest brown dwarfs known. Our 8-hour MIRI low resolution spectroscopy (LRS) and 7-hour NIRSpec prism observations extended variability measurements for any brown dwarfs beyond 11 $μ$m for the first time, reaching up to 14 $μ$m. Combined with the previous epoch in 2023, they set the longest JWST weather monitoring baseline to date. We found that both WISE 1049AB show wavelength-dependent light curve behaviours. Using a robust k-means clustering algorithm, we identified several clusters of variability behaviours associated with three distinct pressure levels. By comparing to a general circulation model (GCM), we identified the possible mechanisms that drive the variability at these pressure levels: Patchy clouds rotating in and out of view likely shaped the dramatic light curves in the deepest layers between 1-2.5 $μ$m, whereas hot spots arising from temperature / chemical variations of molecular species likely dominate the high-altitude levels between 2.5-3.6 $μ$m and 4.3-8.5 $μ$m. Small-grain silicates potentially contributed to the variability of WISE 1049A at 8.5-11 $μ$m. While distinct atmospheric layers are governed by different mechanisms, we confirmed for the first time that each variability mechanism remains consistent within its layer over the long term. Future multi-period observations will further test the stability of variability mechanisms on this binary, and expanded JWST variability surveys across the L-T-Y sequence will allow us to trace and understand variability mechanisms across a wider population of brown dwarfs and planetary-mass objects.

astro-ph.SR↗

A benchmark companion at the hydrogen-burning limit imaged in the core cluster of the Fornax-Horologium association

Low-mass stellar and substellar companions are indispensable objects for verifying evolutionary models that transition from low-mass stars to planets. Their formation is likely also affected by the surrounding stellar environment. The Fornax-Horologium (FH) association is a recently classified young association in the solar neighbourhood with a dissolving open cluster in its centre. It has not been searched widely for substellar companions and exoplanets with direct imaging. We search for companions of stars in the FH and investigate the formation and evolution of companions during the expansion and dissolution of a star cluster. We conduct a direct-imaging survey of 49 stars in FH with VLT/SPHERE. We present HD 24121B, a companion at the hydrogen-burning limit that orbits star HD 24121 in the core cluster of the FH. The companion is located at a projected angular separation of 2.082 $\pm$ 0.004 arcsec from the central star and has contrasts of $Δ$H2 = 5.07 $\pm$ 0.05 mag and $Δ$H3= 4.98 $\pm$ 0.05 mag. We estimate a photometric mass of 74.9 $\pm$ 7.5 $M_J$ for HD 24121B, which places it at the boundary of brown dwarfs and low-mass stars. It is a new benchmark object for evolutionary models at the hydrogen-burning boundary, especially at the age of 30 - 40 Myr. Orbital fitting with joint Gaia and SPHERE relative astrometry found a high eccentricity for HD 24121B. This suggests that it may have undergone dynamic scattering. Future chemical composition measurements such as high-resolution spectroscopic observations will provide more clues on its formation history.

astro-ph.SR↗

A Survey on fMRI-based Brain Decoding for Reconstructing Multimodal Stimuli

In daily life, we encounter diverse external stimuli, such as images, sounds, and videos. As research in multimodal stimuli and neuroscience advances, fMRI-based brain decoding has become a key tool for understanding brain perception and its complex cognitive processes. Decoding brain signals to reconstruct stimuli not only reveals intricate neural mechanisms but also drives progress in AI, disease treatment, and brain-computer interfaces. Recent advancements in neuroimaging and image generation models have significantly improved fMRI-based decoding. While fMRI offers high spatial resolution for precise brain activity mapping, its low temporal resolution and signal noise pose challenges. Meanwhile, techniques like GANs, VAEs, and Diffusion Models have enhanced reconstructed image quality, and multimodal pre-trained models have boosted cross-modal decoding tasks. This survey systematically reviews recent progress in fMRI-based brain decoding, focusing on stimulus reconstruction from passive brain signals. It summarizes datasets, relevant brain regions, and categorizes existing methods by model structure. Additionally, it evaluates model performance and discusses their effectiveness. Finally, it identifies key challenges and proposes future research directions, offering valuable insights for the field. For more information and resources related to this survey, visit https://github.com/LpyNow/BrainDecodingImage.

cs.CV↗

Local Optimization of Quantum Circuits (Extended Version)

Recent advances in quantum architectures and computing have motivated the development of new optimizing compilers for quantum programs or circuits. Even though steady progress has been made, existing quantum optimization techniques remain asymptotically and practically inefficient and are unable to offer guarantees on the quality of the optimization. Because many global quantum circuit optimization problems belong to the complexity class QMA (the quantum analog of NP), it is not clear whether quality and efficiency guarantees can both be achieved. In this paper, we present optimization techniques for quantum programs that can offer both efficiency and quality guarantees. Rather than requiring global optimality, our approach relies on a form of local optimality that requires each and every segment of the circuit to be optimal. We show that the local optimality notion can be attained by a cut-and-meld circuit optimization algorithm. The idea behind the algorithm is to cut a circuit into subcircuits, optimize each subcircuit independently by using a specified "oracle" optimizer, and meld the subcircuits by optimizing across the cuts lazily as needed. We specify the algorithm and prove that it ensures local optimality. To prove efficiency, we show that, under some assumptions, the main optimization phase of the algorithm requires a linear number of calls to the oracle optimizer. We implement and evaluate the local-optimality approach to circuit optimization and compare with the state-of-the-art optimizers. The empirical results show that our cut-and-meld algorithm can outperform existing optimizers significantly, by more than an order of magnitude on average, while also slightly improving optimization quality. These results show that local optimality can be a relatively strong optimization criterion and can be attained efficiently.

cs.PL↗

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems III: Aperture Masking Interferometric Observations of the star HIP 65426 at 3.8 um

We present aperture masking interferometry (AMI) observations of the star HIP 65426 at $3.8\,\rm{μm}$ as a part of the JWST Direct Imaging Early Release Science (ERS) program obtained using the Near Infrared Imager and Slitless Spectrograph (NIRISS) instrument. This mode provides access to very small inner working angles (even separations slightly below the Michelson limit of $0.5λ/D$ for an interferometer), which are inaccessible with the classical inner working angles of the JWST coronagraphs. When combined with JWST's unprecedented infrared sensitivity, this mode has the potential to probe a new portion of parameter space across a wide array of astronomical observations. Using this mode, we are able to achieve a $5σ$ contrast of $Δm{\sim}7.62{\pm}0.13$ mag relative to the host star at separations ${\gtrsim}0.07{"}$, and the contrast deteriorates steeply at separations ${\lesssim}0.07{"}$. However, we detect no additional companions interior to the known companion HIP 65426 b (at separation ${\sim}0.82{"}$ or, $87^{+108}_{-31}\,\rm{au}$). Our observations thus rule out companions more massive than $10{-}12\,\rm{M_{Jup}}$ at separations ${\sim}10{-}20\,\rm{au}$ from HIP 65426, a region out of reach of ground or space-based coronagraphic imaging. These observations confirm that the AMI mode on JWST is sensitive to planetary mass companions at close-in separations (${\gtrsim}0.07{"}$), even for thousands of more distant stars at $\sim$100 pc, in addition to the stars in the nearby young moving groups as stated in previous works. This result will allow the planning and successful execution of future observations to probe the inner regions of nearby stellar systems, opening an essentially unexplored parameter space.

astro-ph.EP↗

QuEst: Graph Transformer for Quantum Circuit Reliability Estimation

Among different quantum algorithms, PQC for QML show promises on near-term devices. To facilitate the QML and PQC research, a recent python library called TorchQuantum has been released. It can construct, simulate, and train PQC for machine learning tasks with high speed and convenient debugging supports. Besides quantum for ML, we want to raise the community's attention on the reversed direction: ML for quantum. Specifically, the TorchQuantum library also supports using data-driven ML models to solve problems in quantum system research, such as predicting the impact of quantum noise on circuit fidelity and improving the quantum circuit compilation efficiency. This paper presents a case study of the ML for quantum part. Since estimating the noise impact on circuit reliability is an essential step toward understanding and mitigating noise, we propose to leverage classical ML to predict noise impact on circuit fidelity. Inspired by the natural graph representation of quantum circuits, we propose to leverage a graph transformer model to predict the noisy circuit fidelity. We firstly collect a large dataset with a variety of quantum circuits and obtain their fidelity on noisy simulators and real machines. Then we embed each circuit into a graph with gate and noise properties as node features, and adopt a graph transformer to predict the fidelity. Evaluated on 5 thousand random and algorithm circuits, the graph transformer predictor can provide accurate fidelity estimation with RMSE error 0.04 and outperform a simple neural network-based model by 0.02 on average. It can achieve 0.99 and 0.95 R$^2$ scores for random and algorithm circuits, respectively. Compared with circuit simulators, the predictor has over 200X speedup for estimating the fidelity.

quant-ph↗

Hardware implementation of timely reliable Bayesian decision-making using memristors

Brains perform decision-making by Bayes theorem. The theorem quantifies events as probabilities and, based on probability rules, renders the decisions. Learning from this, Bayes theorem can be applied to enable efficient user-scene interactions. However, given the probabilistic nature, implementing Bayes theorem in hardware using conventional deterministic computing can incur excessive computational cost and decision latency. Though challenging, here we present a probabilistic computing approach based on memristors to implement the Bayes theorem. We integrate memristors with Boolean logics and, by exploiting the volatile stochastic switching of the memristors, realise probabilistic logic operations, key for hardware Bayes theorem implementation. To empirically validate the efficacy of the hardware Bayes theorem in user-scene interactions, we develop lightweight Bayesian inference and fusion hardware operators using the probabilistic logics and apply the operators in road scene parsing for self-driving, including route planning and obstacle detection. The results show our operators can achieve reliable decisions in less than 0.4 ms (or equivalently 2,500 fps), outperforming human decision-making and the existing driving assistance systems.

cs.LG↗

Analysis on reservoir activation with the nonlinearity harnessed from solution-processed molybdenum disulfide

Reservoir computing is a recurrent neural network designed for approximating complex dynamics in, for instance, motion tracking, spatial-temporal pattern recognition, and chaotic attractor reconstruction. Its implementation demands intense computation for the nonlinear transformation of the reservoir input, i.e. activating the reservoir. Configuring physical nonlinear networks as the reservoir and employing the physical nonlinearity for the reservoir activation is an emergent solution to address the challenge. In this work, we analyze the feasibility of harnessing the nonlinearity from solution-processed molybdenum disulfide (MoS2) for reservoir activation. We fit the high-order nonlinearity, achieved by Stark modulation of MoS2, as the activation function to facilitate implementation of a reservoir computing model. Due to the high-order nonlinearity, the model can achieve long-term synchronization and robust generalization for complex dynamical system regression. As a potential application exploring this ability, we appoint the model to generate chaotic random numbers for secure data encryption. Given this reservoir activation capability, and the scalability of solution-processed MoS2, our results suggest the potential for realizing physical reservoir computing with solution-processed MoS2.

physics.app-ph↗

The JWST Weather Report from the Isolated Exoplanet Analog SIMP 0136+0933: Pressure-Dependent Variability Driven by Multiple Mechanisms

Isolated planetary-mass objects share their mass range with planets but do not orbit a star. They lack the necessary mass to support fusion in their cores and thermally radiate their heat from formation as they cool, primarily at infrared wavelengths. Many isolated planetary-mass objects show variations in their infrared brightness consistent with non-uniform atmospheric features modulated by their rotation. SIMP J013656.5+093347.3 is a rapidly rotating isolated planetary-mass object, and previous infrared monitoring suggests complex atmospheric features rotating in and out of view. The physical nature of these features is not well understood, with clouds, temperature variations, thermochemical instabilities, and infrared-emitting aurora all proposed as contributing mechanisms. Here we report JWST time-resolved low-resolution spectroscopy from 0.8 - 11 micron of SIMP J013656.5+093347.3 which supports the presence of three specific features in the atmosphere: clouds, hot spots, and changing carbon chemistry. We show that no single mechanism can explain the variations in the time-resolved spectra. When combined with previous studies of this object indicating patchy clouds and aurorae, these measurements reveal the rich complexity of the atmosphere of SIMP J013656.5+093347.3. Gas giant planets in the solar system, specifically Jupiter and Saturn, also have multiple cloud layers and high-altitude hot spots, suggesting these phenomena are also present in worlds both within and beyond our solar-system.

astro-ph.EP↗

Atomique: A Quantum Compiler for Reconfigurable Neutral Atom Arrays

The neutral atom array has gained prominence in quantum computing for its scalability and operation fidelity. Previous works focus on fixed atom arrays (FAAs) that require extensive SWAP operations for long-range interactions. This work explores a novel architecture reconfigurable atom arrays (RAAs), also known as field programmable qubit arrays (FPQAs), which allows for coherent atom movements during circuit execution under some constraints. Such atom movements, which are unique to this architecture, could reduce the cost of long-range interactions significantly if the atom movements could be scheduled strategically. In this work, we introduce Atomique, a compilation framework designed for qubit mapping, atom movement, and gate scheduling for RAA. Atomique contains a qubit-array mapper to decide the coarse-grained mapping of the qubits to arrays, leveraging MAX k-Cut on a constructed gate frequency graph to minimize SWAP overhead. Subsequently, a qubit-atom mapper determines the fine-grained mapping of qubits to specific atoms in the array and considers load balance to prevent hardware constraint violations. We further propose a router that identifies parallel gates, schedules them simultaneously, and reduces depth. We evaluate Atomique across 20+ diverse benchmarks, including generic circuits (arbitrary, QASMBench, SupermarQ), quantum simulation, and QAOA circuits. Atomique consistently outperforms IBM Superconducting, FAA with long-range gates, and FAA with rectangular and triangular topologies, achieving significant reductions in depth and the number of two-qubit gates.

quant-ph↗

Harnessing physical entropy noise in structurally metastable 1T' molybdenum ditelluride for true random number generation

True random numbers are essential in various research and engineering problems. Their generation depends upon a robust physical entropy noise. Here, we present true random number generation by harnessing the conductance noise probed in structurally metastable 1T' molybdenum ditelluride (MoTe2). The noise, well-fitting a Poisson process, is proved a robust physical entropy noise at low and even cryogenic temperatures. Noise characteristic analysis suggests the noise may originate from the polarization variations of the underlying ferroelectric dipoles in 1T' MoTe2. We demonstrate the noise allows for true random number generation, enabling their use as seed for generating high-throughput secure random numbers exceeding 1 Mbit/s, appealing for practical applications in, for instance, cryptography where data security is now a severe issue. As an example, we show biometric information safeguarding in neural networks by using the random numbers as mask, proving a promising data security measure in big data and artificial intelligence.

cs.CR↗

Q-Pilot: Field Programmable Qubit Array Compilation with Flying Ancillas

Neutral atom arrays have become a promising platform for quantum computing, especially the field programmable qubit array (FPQA) endowed with the unique capability of atom movement. This feature allows dynamic alterations in qubit connectivity during runtime, which can reduce the cost of executing long-range gates and improve parallelism. However, this added flexibility introduces new challenges in circuit compilation. Inspired by the placement and routing strategies for FPGAs, we propose to map all data qubits to fixed atoms while utilizing movable atoms to route for 2-qubit gates between data qubits. Coined flying ancillas, these mobile atoms function as ancilla qubits, dynamically generated and recycled during execution. We present Q-Pilot, a scalable compiler for FPQA employing flying ancillas to maximize circuit parallelism. For two important quantum applications, quantum simulation and the Quantum Approximate Optimization Algorithm (QAOA), we devise domain-specific routing strategies. In comparison to alternative technologies such as superconducting devices or fixed atom arrays, Q-Pilot effectively harnesses the flexibility of FPQA, achieving reductions of 1.4x, 27.7x, and 6.3x in circuit depth for 100-qubit random, quantum simulation, and QAOA circuits, respectively.

quant-ph↗

The JWST Weather Report from the Nearest Brown Dwarfs I: multi-period JWST NIRSpec + MIRI monitoring of the benchmark binary brown dwarf WISE 1049AB

We report results from 8 hours of JWST/MIRI LRS spectroscopic monitoring directly followed by 7 hours of JWST/NIRSpec prism spectroscopic monitoring of the benchmark binary brown dwarf WISE 1049AB, the closest, brightest brown dwarfs known. We find water, methane, and CO absorption features in both components, including the 3.3 $μ$m methane absorption feature and a tentative detection of small grain ($<$ 1$μ$m) silicate absorption at $>$8.5 $μ$m in WISE 1049A. Both components vary significantly ($>$1$\%$), with WISE 1049B displaying larger variations than WISE 1049A. Using K-means clustering, we find three main transition points in wavelength for both components of the binary: 1) change in behavior at $\sim$2.3 $μ$m coincident with a CO absorption bandhead, 2) change in behavior at 4.2 $μ$m, close to the CO fundamental band at $λ>$ 4.4 $μ$m, and 3) change in behavior at 8.3-8.5 $μ$m, potentially corresponding to silicate absorption. We interpret the lightcurves observed with both NIRSpec and MIRI as likely stemming from 1) a deep pressure level driving the double-peaked variability seen in WISE 1049B at wavelengths $<$2.3 $μ$m and $>$8.5 $μ$m, 2) an intermediate pressure level shaping the lightcurve morphology between 2.3 and 4.2 $μ$m, and 3) a higher-altitude pressure level producing single-peaked and plateaued lightcurve behavior between 4.2 and 8.5 $μ$m.

astro-ph.SR↗

Micro-gesture Online Recognition using Learnable Query Points

In this paper, we briefly introduce the solution developed by our team, HFUT-VUT, for the Micro-gesture Online Recognition track in the MiGA challenge at IJCAI 2024. The Micro-gesture Online Recognition task involves identifying the category and locating the start and end times of micro-gestures in video clips. Compared to the typical Temporal Action Detection task, the Micro-gesture Online Recognition task focuses more on distinguishing between micro-gestures and pinpointing the start and end times of actions. Our solution ranks 2nd in the Micro-gesture Online Recognition track.

cs.CV↗

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems II: A 1 to 20 Micron Spectrum of the Planetary-Mass Companion VHS 1256-1257 b

We present the highest fidelity spectrum to date of a planetary-mass object. VHS 1256 b is a $<$20 M$_\mathrm{Jup}$ widely separated ($\sim$8\arcsec, a = 150 au), young, planetary-mass companion that shares photometric colors and spectroscopic features with the directly imaged exoplanets HR 8799 c, d, and e. As an L-to-T transition object, VHS 1256 b exists along the region of the color-magnitude diagram where substellar atmospheres transition from cloudy to clear. We observed VHS 1256~b with \textit{JWST}'s NIRSpec IFU and MIRI MRS modes for coverage from 1 $μ$m to 20 $μ$m at resolutions of $\sim$1,000 - 3,700. Water, methane, carbon monoxide, carbon dioxide, sodium, and potassium are observed in several portions of the \textit{JWST} spectrum based on comparisons from template brown dwarf spectra, molecular opacities, and atmospheric models. The spectral shape of VHS 1256 b is influenced by disequilibrium chemistry and clouds. We directly detect silicate clouds, the first such detection reported for a planetary-mass companion.

astro-ph.EP↗