9,151 research outputs found
Prospects for Detecting Neutrino Signals from Annihilating/Decaying Dark Matter to Account for the PAMELA and ATIC results
Recent PAMELA data show that positron fraction has an excess above several
GeV while anti-proton one is not. Moreover ATIC data indicates that
electron/positron flux have a bump from 300 GeV to 800 GeV. Both annihilating
dark matter (DM) with large boost factor and decaying DM with the life around can account for the PAMELA and ATIC observations if their main final
products are charged leptons (, and ). In this work, we
calculated the neutrino flux arising from and which originate from
annihilating/decaying DM, and estimated the final muon rate in the neutrino
telescopes, namely Antares and IceCube. Given the excellent angular resolution,
Antares and IceCube are promising to discover the neutrino signals from
Galactic center and/or large DM subhalo in annihilating DM scenario, but very
challenging in decaying DM scenario.Comment: 21 pages, 7 figures, 2 tables. V2: references added. V3: the number
density of massive subhalo has been discussed in the appendix; accepted by
PR
Alignment is not sufficient to prevent large language models from generating harmful information: A psychoanalytic perspective
Large Language Models (LLMs) are central to a multitude of applications but
struggle with significant risks, notably in generating harmful content and
biases. Drawing an analogy to the human psyche's conflict between evolutionary
survival instincts and societal norm adherence elucidated in Freud's
psychoanalysis theory, we argue that LLMs suffer a similar fundamental
conflict, arising between their inherent desire for syntactic and semantic
continuity, established during the pre-training phase, and the post-training
alignment with human values. This conflict renders LLMs vulnerable to
adversarial attacks, wherein intensifying the models' desire for continuity can
circumvent alignment efforts, resulting in the generation of harmful
information. Through a series of experiments, we first validated the existence
of the desire for continuity in LLMs, and further devised a straightforward yet
powerful technique, such as incomplete sentences, negative priming, and
cognitive dissonance scenarios, to demonstrate that even advanced LLMs struggle
to prevent the generation of harmful information. In summary, our study
uncovers the root of LLMs' vulnerabilities to adversarial attacks, hereby
questioning the efficacy of solely relying on sophisticated alignment methods,
and further advocates for a new training idea that integrates modal concepts
alongside traditional amodal concepts, aiming to endow LLMs with a more nuanced
understanding of real-world contexts and ethical considerations
U(1)-decoupling, KK and BCJ relations in SYM
We proved the color reflection relation, U(1)-decoupling, Kleiss-Kuijf and
Bern-Carrasco-Johansson relation for color-ordered Super
Yang-Mills theory using SYM version BCFW recursion relation,
which depends only on the general properties of super-amplitudes. This verified
the conjectured matter fields BCJ relation. We also show that color reflection
relation and U(1)-decoupling relation are special cases of KK relation, if we
consider the KK relation as a general relation, then the former two relations
come out naturally as the special cases.Comment: 17 page
Discriminating different scenarios to account for the cosmic excess by synchrotron and inverse Compton radiation
The excesses of the cosmic positron fraction recently measured by PAMELA and
the electron spectra by ATIC, PPB-BETS, Fermi and H.E.S.S. indicate the
existence of primary electron and positron sources. The possible explanations
include dark matter annihilation, decay, and astrophysical origin, like
pulsars. In this work we show that these three scenarios can all explain the
experimental results of the cosmic excess. However, it may be difficult
to discriminate these different scenarios by the local measurements of
electrons and positrons. We propose possible discriminations among these
scenarios through the synchrotron and inverse Compton radiation of the primary
electrons/positrons from the region close to the Galactic center. Taking
typical configurations, we find the three scenarios predict quite different
spectra and skymaps of the synchrotron and inverse Compton radiation, though
there are relatively large uncertainties. The most prominent differences come
from the energy band MHz for synchrotron emission and GeV for inverse Compton emission. It might be able to discriminate at least
the annihilating dark matter scenario from the other two given the high
precision synchrotron and diffuse -ray skymaps in the future.Comment: published in Pr
Diagnosing the possible chiral superconductivity in SrRuO and beyond using supercurrent
One approach to probe the still controversial superconductivity in
SrRuO is to apply external perturbations that break the underlying
tetragonal crystalline symmetry. Chiral and states
respond to such perturbations in ways that may help to distinguish them from
other superconducting pairings. However, past experimental efforts along this
line, using uniaxial strains and magnetic fields parallel to the RuO plane,
have not been able to reach unambiguous conclusion. In this study, we propose
to diagnose the possible chiral superconducting order in SrRuO using an
alternative tetragonal-symmetry-breaking perturbation -- in-plane supercurrent.
We study the superconducting phase diagram as a function of both temperature
and the applied supercurrent. Supercurrent generically splits the transition of
the two chiral order parameter components, and we show that the splitting can
give rise to visible specific heat anomalies. Furthermore, supercurrent
parallel and anti-parallel to the unidirectional propagation of the chiral edge
modes impact the edge states in different manner. This difference manifests in
tunneling spectrum, thereby providing an additional means to probe the
chirality even when the related spontaneous edge current is vanishingly small.
Finally, we discuss how supercurrent may help to identity other time-reversal
symmetry breaking superconducting states. Our proposal applies to other
candidate chiral superconductors.Comment: 7 pages, 7 figure
Emotional Intelligence of Large Language Models
Large Language Models (LLMs) have demonstrated remarkable abilities across
numerous disciplines, primarily assessed through tasks in language generation,
knowledge utilization, and complex reasoning. However, their alignment with
human emotions and values, which is critical for real-world applications, has
not been systematically evaluated. Here, we assessed LLMs' Emotional
Intelligence (EI), encompassing emotion recognition, interpretation, and
understanding, which is necessary for effective communication and social
interactions. Specifically, we first developed a novel psychometric assessment
focusing on Emotion Understanding (EU), a core component of EI, suitable for
both humans and LLMs. This test requires evaluating complex emotions (e.g.,
surprised, joyful, puzzled, proud) in realistic scenarios (e.g., despite
feeling underperformed, John surprisingly achieved a top score). With a
reference frame constructed from over 500 adults, we tested a variety of
mainstream LLMs. Most achieved above-average EQ scores, with GPT-4 exceeding
89% of human participants with an EQ of 117. Interestingly, a multivariate
pattern analysis revealed that some LLMs apparently did not reply on the
human-like mechanism to achieve human-level performance, as their
representational patterns were qualitatively distinct from humans. In addition,
we discussed the impact of factors such as model size, training method, and
architecture on LLMs' EQ. In summary, our study presents one of the first
psychometric evaluations of the human-like characteristics of LLMs, which may
shed light on the future development of LLMs aiming for both high intellectual
and emotional intelligence. Project website:
https://emotional-intelligence.github.io/Comment: 34 pages, 4 figure
SRoUDA: Meta Self-training for Robust Unsupervised Domain Adaptation
As acquiring manual labels on data could be costly, unsupervised domain
adaptation (UDA), which transfers knowledge learned from a rich-label dataset
to the unlabeled target dataset, is gaining increasing popularity. While
extensive studies have been devoted to improving the model accuracy on target
domain, an important issue of model robustness is neglected. To make things
worse, conventional adversarial training (AT) methods for improving model
robustness are inapplicable under UDA scenario since they train models on
adversarial examples that are generated by supervised loss function. In this
paper, we present a new meta self-training pipeline, named SRoUDA, for
improving adversarial robustness of UDA models. Based on self-training
paradigm, SRoUDA starts with pre-training a source model by applying UDA
baseline on source labeled data and taraget unlabeled data with a developed
random masked augmentation (RMA), and then alternates between adversarial
target model training on pseudo-labeled target data and finetuning source model
by a meta step. While self-training allows the direct incorporation of AT in
UDA, the meta step in SRoUDA further helps in mitigating error propagation from
noisy pseudo labels. Extensive experiments on various benchmark datasets
demonstrate the state-of-the-art performance of SRoUDA where it achieves
significant model robustness improvement without harming clean accuracy. Code
is available at https://github.com/Vision.Comment: This paper has been accepted for presentation at the AAAI202
Decacarbonyl[μ4-(ethane-1,2-diyldinitrilo)tetrakis(methanethiolato)]bis(triphenylphosphane)tetrairon(2 Fe—Fe)
In the title compound, [Fe4(C6H12N2S4)(C18H15P)2(CO)10], the unit cell contains one molecule, which exhibits a crystallographically imposed center of symmetry. The independent Fe2S2 fragment [Fe—Fe = 2.527 (1) Å] is in a butterfly conformation, and each Fe atom displays a pseudo-square-pyramidal coordination geometry. The phosphane group occupies an apical position [Fe—P = 2.2670 (14) Å]. In the crystal, weak intermolecular C—H⋯O hydrogen bonds link the molecules into chains along [110]
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