arXiv subjects

Pengyu Liu

Publications and source records attributed to Pengyu Liu.

At least 55 records · Page 3Linked to original sources

arXiv2024

Prioritizing High-Precision Photometric Monitoring of Exoplanet and Brown Dwarf Companions with JWST -- Strategic Exoplanet Initiatives with HST and JWST White Paper

We advocate for the prioritization of high-precision photometric monitoring of exoplanet and brown dwarf companions to detect brightness variability arising from features in their atmospheres. Measurements of photometric variability provide not only an insight into the physical appearances of these companions, but are also a direct probe of their atmospheric structures and dynamics, and yield valuable estimates of their rotation periods. JWST is uniquely capable of monitoring faint exoplanet companions over their full rotation periods, thanks to its inherent stability and powerful high-contrast coronagraphic imaging modes. Rotation period measurements can be further combined with measurements of v sin i obtained using high-resolution spectroscopy to infer the viewing angle of a companion. Photometric monitoring over multiple rotation periods and at multiple epochs will allow both short- and long-term time evolution in variability signals to be traced. Furthermore, the differences between the layers in a companion's atmosphere can be probed by obtaining simultaneous photometric monitoring at different wavelengths through NIRCam dual-band coronagraphy. Overall, JWST will reach the highest sensitivities to variability to date and enable the light curves of substellar companions to be characterised with unprecedented cadence and precision at the sub-percent level.

astro-ph.IM↗

arXiv2024

DGR: Tackling Drifted and Correlated Noise in Quantum Error Correction via Decoding Graph Re-weighting

Quantum hardware suffers from high error rates and noise, which makes directly running applications on them ineffective. Quantum Error Correction (QEC) is a critical technique towards fault tolerance which encodes the quantum information distributively in multiple data qubits and uses syndrome qubits to check parity. Minimum-Weight-Perfect-Matching (MWPM) is a popular QEC decoder that takes the syndromes as input and finds the matchings between syndromes that infer the errors. However, there are two paramount challenges for MWPM decoders. First, as noise in real quantum systems can drift over time, there is a potential misalignment with the decoding graph's initial weights, leading to a severe performance degradation in the logical error rates. Second, while the MWPM decoder addresses independent errors, it falls short when encountering correlated errors typical on real hardware, such as those in the 2Q depolarizing channel. We propose DGR, an efficient decoding graph edge re-weighting strategy with no quantum overhead. It leverages the insight that the statistics of matchings across decoding iterations offer rich information about errors on real quantum hardware. By counting the occurrences of edges and edge pairs in decoded matchings, we can statistically estimate the up-to-date probabilities of each edge and the correlations between them. The reweighting process includes two vital steps: alignment re-weighting and correlation re-weighting. The former updates the MWPM weights based on statistics to align with actual noise, and the latter adjusts the weight considering edge correlations. Extensive evaluations on surface code and honeycomb code under various settings show that DGR reduces the logical error rate by 3.6x on average-case noise mismatch with exceeding 5000x improvement under worst-case mismatch.

quant-ph↗

arXiv2024

Lightweight, error-tolerant edge detection using memristor-enabled stochastic logics

The demand for efficient edge vision has spurred the interest in developing stochastic computing approaches for performing image processing tasks. Memristors with inherent stochasticity readily introduce probability into the computations and thus enable stochastic image processing computations. Here, we present a stochastic computing approach for edge detection, a fundamental image processing technique, facilitated with memristor-enabled stochastic logics. Specifically, we integrate the memristors with logic circuits and harness the stochasticity from the memristors to realize compact stochastic logics for stochastic number encoding and processing. The stochastic numbers, exhibiting well-regulated probabilities and correlations, can be processed to perform logic operations with statistical probabilities. This can facilitate lightweight stochastic edge detection for edge visual scenarios characterized with high-level noise errors. As a practical demonstration, we implement a hardware stochastic Roberts cross operator using the stochastic logics, and prove its exceptional edge detection performance, remarkably, with 95% less computational cost while withstanding 50% bit-flip errors. The results underscore the great potential of our stochastic edge detection approach in developing lightweight, error-tolerant edge vision hardware and systems for autonomous driving, virtual/augmented reality, medical imaging diagnosis, industrial automation, and beyond.

cs.ET↗

arXiv2024

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems IV: NIRISS Aperture Masking Interferometry Performance and Lessons Learned

We present a performance analysis for the aperture masking interferometry (AMI) mode on board the James Webb Space Telescope Near Infrared Imager and Slitless Spectrograph (JWST/NIRISS). Thanks to self-calibrating observables, AMI accesses inner working angles down to and even within the classical diffraction limit. The scientific potential of this mode has recently been demonstrated by the Early Release Science (ERS) 1386 program with a deep search for close-in companions in the HIP 65426 exoplanetary system. As part of ERS 1386, we use the same data set to explore the random, static, and calibration errors of NIRISS AMI observables. We compare the observed noise properties and achievable contrast to theoretical predictions. We explore possible sources of calibration errors and show that differences in charge migration between the observations of HIP 65426 and point-spread function calibration stars can account for the achieved contrast curves. Lastly, we use self-calibration tests to demonstrate that with adequate calibration NIRISS F380M AMI can reach contrast levels of $\sim9-10$ mag at $\gtrsim λ/D$. These tests lead us to observation planning recommendations and strongly motivate future studies aimed at producing sophisticated calibration strategies taking these systematic effects into account. This will unlock the unprecedented capabilities of JWST/NIRISS AMI, with sensitivity to significantly colder, lower-mass exoplanets than lower-contrast ground-based AMI setups, at orbital separations inaccessible to JWST coronagraphy.

astro-ph.EP↗

arXiv2024

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems V: Do Self-Consistent Atmospheric Models Represent JWST Spectra? A Showcase With VHS 1256 b

The unprecedented medium-resolution (R~1500-3500) near- and mid-infrared (1-18um) spectrum provided by JWST for the young (140+/-20Myr) low-mass (12-20MJup) L-T transition (L7) companion VHS1256b gives access to a catalogue of molecular absorptions. In this study, we present a comprehensive analysis of this dataset utilizing a forward modelling approach, applying our Bayesian framework, ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters: Teff, log(g), [M/H], C/O, gamma, fsed, and R. Our findings reveal that each parameter's estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS1256b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived a Teff consistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST's data for VHS1256b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models.

astro-ph.EP↗

arXiv2023

A Near-infrared Variability Survey of Young Planetary-mass Objects

We present a photometric variability survey of young planetary-mass objects using the New Technology Telescope in the Js and Ks bands. Surface gravity plays an important role in the atmospheric structure of brown dwarfs, as young low gravity L dwarfs have a higher variability rate than field L dwarfs. In this study, we extend variability studies to young T-type planetary-mass objects and investigate the effects of surface gravity on the variability of L and T dwarfs across a large sample. We conduct continuous monitoring for 18 objects with spectral types from L5 to T8 and detect four new variables and two variable candidates. Combining with previous variability surveys of field and young L and T objects, we find that young objects tend to be more variable than field objects within peak-to-peak variability amplitude ranges of 0.5-10 per cent and period ranges of 1.5-20 hr. For the first time, we constrain the variability rate of young T dwarfs to be 56 per cent compared to 25 per cent for field T dwarfs. Both field and young samples have higher variability rates at the L/T transition than outside the L/T transition. The differences in the variability rates between field and young samples are about 1 sigma and therefore larger sample sizes are needed to confirm and refine the results. Besides the L/T transition, young L dwarfs with strong variability tend to assemble in a narrow spectral type range of L6-L7.5. This work supports the critical role of surface gravity on the atmospheric structure from L to T spectral types.

astro-ph.EP↗

arXiv2023

RobustState: Boosting Fidelity of Quantum State Preparation via Noise-Aware Variational Training

Quantum state preparation, a crucial subroutine in quantum computing, involves generating a target quantum state from initialized qubits. Arbitrary state preparation algorithms can be broadly categorized into arithmetic decomposition (AD) and variational quantum state preparation (VQSP). AD employs a predefined procedure to decompose the target state into a series of gates, whereas VQSP iteratively tunes ansatz parameters to approximate target state. VQSP is particularly apt for Noisy-Intermediate Scale Quantum (NISQ) machines due to its shorter circuits. However, achieving noise-robust parameter optimization still remains challenging. We present RobustState, a novel VQSP training methodology that combines high robustness with high training efficiency. The core idea involves utilizing measurement outcomes from real machines to perform back-propagation through classical simulators, thus incorporating real quantum noise into gradient calculations. RobustState serves as a versatile, plug-and-play technique applicable for training parameters from scratch or fine-tuning existing parameters to enhance fidelity on target machines. It is adaptable to various ansatzes at both gate and pulse levels and can even benefit other variational algorithms, such as variational unitary synthesis. Comprehensive evaluation of RobustState on state preparation tasks for 4 distinct quantum algorithms using 10 real quantum machines demonstrates a coherent error reduction of up to 7.1 $\times$ and state fidelity improvement of up to 96\% and 81\% for 4-Q and 5-Q states, respectively. On average, RobustState improves fidelity by 50\% and 72\% for 4-Q and 5-Q states compared to baseline approaches.

quant-ph↗

arXiv2023

Transformer-QEC: Quantum Error Correction Code Decoding with Transferable Transformers

Quantum computing has the potential to solve problems that are intractable for classical systems, yet the high error rates in contemporary quantum devices often exceed tolerable limits for useful algorithm execution. Quantum Error Correction (QEC) mitigates this by employing redundancy, distributing quantum information across multiple data qubits and utilizing syndrome qubits to monitor their states for errors. The syndromes are subsequently interpreted by a decoding algorithm to identify and correct errors in the data qubits. This task is complex due to the multiplicity of error sources affecting both data and syndrome qubits as well as syndrome extraction operations. Additionally, identical syndromes can emanate from different error sources, necessitating a decoding algorithm that evaluates syndromes collectively. Although machine learning (ML) decoders such as multi-layer perceptrons (MLPs) and convolutional neural networks (CNNs) have been proposed, they often focus on local syndrome regions and require retraining when adjusting for different code distances. We introduce a transformer-based QEC decoder which employs self-attention to achieve a global receptive field across all input syndromes. It incorporates a mixed loss training approach, combining both local physical error and global parity label losses. Moreover, the transformer architecture's inherent adaptability to variable-length inputs allows for efficient transfer learning, enabling the decoder to adapt to varying code distances without retraining. Evaluation on six code distances and ten different error configurations demonstrates that our model consistently outperforms non-ML decoders, such as Union Find (UF) and Minimum Weight Perfect Matching (MWPM), and other ML decoders, thereby achieving best logical error rates. Moreover, the transfer learning can save over 10x of training cost.

quant-ph↗

arXiv2023

SimuQ: A Framework for Programming Quantum Hamiltonian Simulation with Analog Compilation

Quantum Hamiltonian simulation, which simulates the evolution of quantum systems and probes quantum phenomena, is one of the most promising applications of quantum computing. Recent experimental results suggest that Hamiltonian-oriented analog quantum simulation would be advantageous over circuit-oriented digital quantum simulation in the Noisy Intermediate-Scale Quantum (NISQ) machine era. However, programming analog quantum simulators is much more challenging due to the lack of a unified interface between hardware and software. In this paper, we design and implement SimuQ, the first framework for quantum Hamiltonian simulation that supports Hamiltonian programming and pulse-level compilation to heterogeneous analog quantum simulators. Specifically, in SimuQ, front-end users specify the target quantum system with Hamiltonian Modeling Language, and the Hamiltonian-level programmability of analog quantum simulators is specified through a new abstraction called the abstract analog instruction set (AAIS) and programmed in AAIS Specification Language by hardware providers. Through a solver-based compilation, SimuQ generates executable pulse schedules for real devices to simulate the evolution of desired quantum systems, which is demonstrated on superconducting (IBM), neutral-atom (QuEra), and trapped-ion (IonQ) quantum devices. Moreover, we demonstrate the advantages of exposing the Hamiltonian-level programmability of devices with native operations or interaction-based gates and establish a small benchmark of quantum simulation to evaluate SimuQ's compiler with the above analog quantum simulators.

cs.PL↗

arXiv2023

Conduction modulation of solution-processed two-dimensional materials

Solution-processed two-dimensional (2D) materials hold promise for their scalable applications. However, the random, fragmented nature of the solution-processed nanoflakes and the poor percolative conduction through their discrete networks limit the performance of the enabled devices. To overcome the problem, we report conduction modulation of the solution-processed 2D materials via the Stark effect. Using liquid-phase exfoliated molybdenum disulfide (MoS2) as an example, we demonstrate nonlinear conduction modulation with a switching ratio of >105 by the local fields from the interfacial ferroelectric P(VDF-TrFE). Through density-functional theory calculations and in situ Raman scattering and photoluminescence spectroscopic analysis, we understand the modulation arises from a charge redistribution in the solution-processed MoS2. Beyond MoS2, we show the modulation may be viable for the other solution-processed 2D materials and low-dimensional materials. The effective modulation can open their electronic device applications.

physics.app-ph↗

arXiv2023

The JWST Early Release Science Program for Direct Observations of Exoplanetary Systems I: High Contrast Imaging of the Exoplanet HIP 65426 b from 2-16 $μ$m

We present JWST Early Release Science (ERS) coronagraphic observations of the super-Jupiter exoplanet, HIP 65426 b, with the Near-Infrared Camera (NIRCam) from 2-5 $μ$m, and with the Mid-Infrared Instrument (MIRI) from 11-16 $μ$m. At a separation of $\sim$0.82" (86$^{+116}_{-31}$ au), HIP 65426 b is clearly detected in all seven of our observational filters, representing the first images of an exoplanet to be obtained by JWST, and the first ever direct detection of an exoplanet beyond 5 $μ$m. These observations demonstrate that JWST is exceeding its nominal predicted performance by up to a factor of 10, depending on separation and subtraction method, with measured 5$σ$ contrast limits of $\sim$1$\times10^{-5}$ and $\sim$2$\times10^{-4}$ at 1" for NIRCam at 4.4 $μ$m and MIRI at 11.3 $μ$m, respectively. These contrast limits provide sensitivity to sub-Jupiter companions with masses as low as 0.3$M_\mathrm{Jup}$ beyond separations of $\sim$100 au. Together with existing ground-based near-infrared data, the JWST photometry are well fit by a BT-SETTL atmospheric model from 1-16 $μ$m, and span $\sim$97% of HIP 65426 b's luminous range. Independent of the choice of model atmosphere we measure an empirical bolometric luminosity that is tightly constrained between $\mathrm{log}\!\left(L_\mathrm{bol}/L_{\odot}\right)$=-4.31 to $-$4.14, which in turn provides a robust mass constraint of 7.1$\pm$1.2 $M_\mathrm{Jup}$. In totality, these observations confirm that JWST presents a powerful and exciting opportunity to characterise the population of exoplanets amenable to high-contrast imaging in greater detail.

astro-ph.EP↗

arXiv2023

Applying a temporal systematics model to vector Apodizing Phase Plate coronagraphic data: TRAP4vAPP

The vector Apodizing Phase Plate (vAPP) is a pupil plane coronagraph that suppresses starlight by forming a dark hole in its point spread function (PSF). The unconventional and non-axisymmetrical PSF arising from the phase modification applied by this coronagraph presents a special challenge to post-processing techniques. We aim to implement a recently developed post-processing algorithm, temporal reference analysis of planets (TRAP) on vAPP coronagraphic data. The property of TRAP that uses non-local training pixels, combined with the unconventional PSF of vAPP, allows for more flexibility than previous spatial algorithms in selecting reference pixels to model systematic noise. Datasets from two types of vAPPs are analysed: a double grating-vAPP (dgvAPP360) that produces a single symmetric PSF and a grating-vAPP (gvAPP180) that produces two D-shaped PSFs. We explore how to choose reference pixels to build temporal systematic noise models in TRAP for them. We then compare the performance of TRAP with previously implemented algorithms that produced the best signal-to-noise ratio (S/N) in companion detections in these datasets. We find that the systematic noise between the two D-shaped PSFs is not as temporally associated as expected. Conversely, there is still a significant number of systematic noise sources that are shared by the dark hole and the bright side in the same PSF. We should choose reference pixels from the same PSF when reducing the dgvAPP360 dataset or the gvAPP180 dataset with TRAP. In these datasets, TRAP achieves results consistent with previous best detections, with an improved S/N for the gvAPP180 dataset.

astro-ph.IM↗

arXiv2023

Detecting entanglement in quantum many-body systems via permutation moments

Multipartite entanglement plays an essential role in both quantum information science and many-body physics. Due to the exponentially large dimension and complex geometric structure of the state space, the detection of entanglement in many-body systems is extremely challenging in reality. Conventional means, like entanglement witness and entropy criterion, either highly depend on the prior knowledge of the studied systems or the detection capability is relatively weak. In this work, we propose a framework for designing multipartite entanglement criteria based on permutation moments, which have an effective implementation with either the generalized control-SWAP quantum circuits or the random unitary techniques. These criteria show strong detection capability in the multi-qubit Ising model with a long-range $XY$ Hamiltonian. The quantities associated with these criteria have clear physical meaning and can be used as entanglement quantifiers, with which we show the entanglement scaling transition in a quantum dynamical phase transition. Furthermore, our framework can also be generalized to detect the much more complicated entanglement structure in quantum many-body systems.

quant-ph↗

arXiv2023

A Generalized Hamming Distance of Sequence Patterns

We define sequence patterns of length $n$ and level $\ell$ to be equivalence classes of sequences that have $n$ elements from the set of $\ell$ integer symbols $\{1,2,\ldots,\ell\}$ with no restriction on repetition, where the equivalence relation is induced by symbol relabeling without swapping positions of symbols. We define a distance for a set of $k$ sequence patterns of length $n$ and level $\ell$ by generalizing the Hamming distance between sequences. We compute the maximal distance for $k$ sequence patterns of length $n$ and level $\ell$ and demonstrate how to calculate the exact distance between a pair of length-$n$ level-$\ell$ sequence patterns.

math.CO↗

arXiv2022

Fundamental Limitation on the Detectability of Entanglement

Entanglement detection is essential in quantum information science and quantum many-body physics. It has been proved that entanglement exists almost surely for a random quantum state, while the realizations of effective entanglement criteria usually consume exponential resources, and efficient criteria often perform poorly without prior knowledge. This fact implies a fundamental limitation might exist in the detectability of entanglement. In this work, we formalize this limitation as a fundamental trade-off between the efficiency and effectiveness of entanglement criteria via a systematic method to theoretically evaluate the detection capability of entanglement criteria. For a system coupled to an environment, we prove that any entanglement criterion needs exponentially many observables to detect the entanglement effectively when restricted to single-copy operations. Otherwise, the detection capability of the criterion will decay double-exponentially. Furthermore, if multi-copy joint measurements are allowed, the effectiveness of entanglement detection can be exponentially improved, which implies a quantum advantage in entanglement detection problems.

quant-ph↗

arXiv2022

Quantifying syntax similarity with a polynomial representation of dependency trees

We introduce a graph polynomial that distinguishes tree structures to represent dependency grammar and a measure based on the polynomial representation to quantify syntax similarity. The polynomial encodes accurate and comprehensive information about the dependency structure and dependency relations of words in a sentence. We apply the polynomial-based methods to analyze sentences in the Parallel Universal Dependencies treebanks. Specifically, we compare the syntax of sentences and their translations in different languages, and we perform a syntactic typology study of available languages in the Parallel Universal Dependencies treebanks. We also demonstrate and discuss the potential of the methods in measuring syntax diversity of corpora.

cs.CL↗

arXiv2022

On The Unusual Variability of 2MASS J06195260-2903592: A Long-Lived Disk around a Young Ultracool Dwarf

We present the characterization of the low-gravity M6 dwarf 2MASS J0619-2903 previously identified as an unusual field object based on its strong IR excess and variable near-IR spectrum. Multiple epochs of low-resolution (R~150) near-IR spectra show large-amplitude (~0.1-0.5 mag) continuum variations on timescales of days to 12 years, unlike the small-amplitude variability typical for field ultracool dwarfs. The variations between epochs are well-modeled as changes in the relative extinction ($Δ{A_V}\approx2$ mag). Likewise, Pan-STARRS optical photometry varies on timescales as long as 11 years (and possibly as short as an hour) and implies similar amplitude $A_V$ changes. NEOWISE mid-IR light curves also suggest changes on 6-month timescales, with amplitudes consistent with the optical/near-IR extinction variations. However, near-IR spectra, near-IR photometry, and optical photometry obtained in the past year indicate the source can also be stable on hourly and monthly timescales. From comparison to objects of similar spectral type, the total extinction of 2MASS J0619-2903 seems to be $A_V\approx4-6$ mag, with perhaps epochs of lower extinction. Gaia EDR3 finds that 2MASS J0619-2903 has a wide-separation (1.2' = 10450 AU) stellar companion, with an isochronal age of $31^{+22}_{-10}$ Myr and a mass of $0.30^{+0.04}_{-0.03}$ Msun. Adopting this companion's age and EDR3 distance (145.2$\pm$0.6 pc), we estimate a mass of 0.11-0.17 Msun for 2MASS J0619-2903. Altogether, 2MASS J0619-2903 appears to possess an unusually long-lived primordial circumstellar disk, perhaps making it a more obscured analog to the "Peter Pan" disks found around a few M dwarfs in nearby young moving groups.

astro-ph.SR↗

arXiv2022

Effects of network topology and trait distribution on collective decision making

Social networks play an important role in analyzing the impact of individual-level interactions on societal or economic outcomes. We model interactive decision making for a community of individuals with different traits, represented by a social network with trait-attributed nodes. We develop a deterministic process generating a sequence of choices for each individual based on a trait-attributed social network, initial choices of individuals and a set of predetermined trait-dependent rules for making decisions. The object of interest is the sequence of cumulative sum of choices over all individuals, which we call the cumulative sequence and consider as an index of collective decisions. We observe that, in a time period, a cumulative sequence can be unpredictable or predictable showing a repeated pattern either escalating to an extreme or constantly oscillating. We consider that predictable cumulative sequences represent unstable collective decisions of communities either extremizing or internally conflicting, while unpredictable cumulative sequences show stable changes. We analyze the effects of network topology and trait distribution on the probability of cumulative sequences being predictable, escalating and oscillating by simulations. Our findings include that unstable collective decisions are more probable as network density increases, that centralized networks are more likely to have unstable collective decisions and that networks with excessively clustered or scattered conformists and rebels tend to produce unstable cumulative sequences. We discuss the potential of the model as a framework for studying individuals with different traits on a social network directly and indirectly interacting in decision making.

physics.soc-ph↗