Showing 1–18 of 18 results for author: Handa, K

Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions

Authors: Saffron Huang, Esin Durmus, Miles McCain, Kunal Handa, Alex Tamkin, Jerry Hong, Michael Stern, Arushi Somani, Xiuruo Zhang, Deep Ganguli

Abstract: AI assistants can impart value judgments that shape people's decisions and worldviews, yet little is known empirically about what values these systems rely on in practice. To address this, we develop a bottom-up, privacy-preserving method to extract the values (normative considerations stated or demonstrated in model responses) that Claude 3 and 3.5 models exhibit in hundreds of thousands of real-… ▽ More AI assistants can impart value judgments that shape people's decisions and worldviews, yet little is known empirically about what values these systems rely on in practice. To address this, we develop a bottom-up, privacy-preserving method to extract the values (normative considerations stated or demonstrated in model responses) that Claude 3 and 3.5 models exhibit in hundreds of thousands of real-world interactions. We empirically discover and taxonomize 3,307 AI values and study how they vary by context. We find that Claude expresses many practical and epistemic values, and typically supports prosocial human values while resisting values like "moral nihilism". While some values appear consistently across contexts (e.g. "transparency"), many are more specialized and context-dependent, reflecting the diversity of human interlocutors and their varied contexts. For example, "harm prevention" emerges when Claude resists users, "historical accuracy" when responding to queries about controversial events, "healthy boundaries" when asked for relationship advice, and "human agency" in technology ethics discussions. By providing the first large-scale empirical mapping of AI values in deployment, our work creates a foundation for more grounded evaluation and design of values in AI systems. △ Less

Submitted 21 April, 2025; originally announced April 2025.

Comments: 44 pages

Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations

Authors: Kunal Handa, Alex Tamkin, Miles McCain, Saffron Huang, Esin Durmus, Sarah Heck, Jared Mueller, Jerry Hong, Stuart Ritchie, Tim Belonax, Kevin K. Troy, Dario Amodei, Jared Kaplan, Jack Clark, Deep Ganguli

Abstract: Despite widespread speculation about artificial intelligence's impact on the future of work, we lack systematic empirical evidence about how these systems are actually being used for different tasks. Here, we present a novel framework for measuring AI usage patterns across the economy. We leverage a recent privacy-preserving system to analyze over four million Claude.ai conversations through the l… ▽ More Despite widespread speculation about artificial intelligence's impact on the future of work, we lack systematic empirical evidence about how these systems are actually being used for different tasks. Here, we present a novel framework for measuring AI usage patterns across the economy. We leverage a recent privacy-preserving system to analyze over four million Claude.ai conversations through the lens of tasks and occupations in the U.S. Department of Labor's O*NET Database. Our analysis reveals that AI usage primarily concentrates in software development and writing tasks, which together account for nearly half of all total usage. However, usage of AI extends more broadly across the economy, with approximately 36% of occupations using AI for at least a quarter of their associated tasks. We also analyze how AI is being used for tasks, finding 57% of usage suggests augmentation of human capabilities (e.g., learning or iterating on an output) while 43% suggests automation (e.g., fulfilling a request with minimal human involvement). While our data and methods face important limitations and only paint a picture of AI usage on a single platform, they provide an automated, granular approach for tracking AI's evolving role in the economy and identifying leading indicators of future impact as these technologies continue to advance. △ Less

Submitted 10 February, 2025; originally announced March 2025.

Clio: Privacy-Preserving Insights into Real-World AI Use

Authors: Alex Tamkin, Miles McCain, Kunal Handa, Esin Durmus, Liane Lovitt, Ankur Rathi, Saffron Huang, Alfred Mountfield, Jerry Hong, Stuart Ritchie, Michael Stern, Brian Clarke, Landon Goldberg, Theodore R. Sumers, Jared Mueller, William McEachen, Wes Mitchell, Shan Carter, Jack Clark, Jared Kaplan, Deep Ganguli

Abstract: How are AI assistants being used in the real world? While model providers in theory have a window into this impact via their users' data, both privacy concerns and practical challenges have made analyzing this data difficult. To address these issues, we present Clio (Claude insights and observations), a privacy-preserving platform that uses AI assistants themselves to analyze and surface aggregate… ▽ More How are AI assistants being used in the real world? While model providers in theory have a window into this impact via their users' data, both privacy concerns and practical challenges have made analyzing this data difficult. To address these issues, we present Clio (Claude insights and observations), a privacy-preserving platform that uses AI assistants themselves to analyze and surface aggregated usage patterns across millions of conversations, without the need for human reviewers to read raw conversations. We validate this can be done with a high degree of accuracy and privacy by conducting extensive evaluations. We demonstrate Clio's usefulness in two broad ways. First, we share insights about how models are being used in the real world from one million Claude.ai Free and Pro conversations, ranging from providing advice on hairstyles to providing guidance on Git operations and concepts. We also identify the most common high-level use cases on Claude.ai (coding, writing, and research tasks) as well as patterns that differ across languages (e.g., conversations in Japanese discuss elder care and aging populations at higher-than-typical rates). Second, we use Clio to make our systems safer by identifying coordinated attempts to abuse our systems, monitoring for unknown unknowns during critical periods like launches of new capabilities or major world events, and improving our existing monitoring systems. We also discuss the limitations of our approach, as well as risks and ethical concerns. By enabling analysis of real-world AI usage, Clio provides a scalable platform for empirically grounded AI safety and governance. △ Less

Submitted 18 December, 2024; originally announced December 2024.

Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy

Authors: Benedict Aaron Tjandra, Muhammed Razzak, Jannik Kossen, Kunal Handa, Yarin Gal

Abstract: Large Language Models (LLMs) are known to hallucinate, whereby they generate plausible but inaccurate text. This phenomenon poses significant risks in critical applications, such as medicine or law, necessitating robust hallucination mitigation strategies. While recent works have proposed fine-tuning methods to teach LLMs to abstain from answering questions beyond their knowledge or capabilities,… ▽ More Large Language Models (LLMs) are known to hallucinate, whereby they generate plausible but inaccurate text. This phenomenon poses significant risks in critical applications, such as medicine or law, necessitating robust hallucination mitigation strategies. While recent works have proposed fine-tuning methods to teach LLMs to abstain from answering questions beyond their knowledge or capabilities, these methods rely on the existence of ground-truth labels or are limited to short-form responses. To address these limitations, we propose fine-tuning using semantic entropy, an uncertainty measure derived from introspection into the model which does not require external labels. We demonstrate that our approach matches or outperforms models fine-tuned using prior work and achieves strong performance for both short and long-form generations on a range of datasets. △ Less

Submitted 22 October, 2024; originally announced October 2024.

Comments: Accepted to NeurIPS Safe Generative AI Workshop 2024

Bayesian Preference Elicitation with Language Models

Authors: Kunal Handa, Yarin Gal, Ellie Pavlick, Noah Goodman, Jacob Andreas, Alex Tamkin, Belinda Z. Li

Abstract: Aligning AI systems to users' interests requires understanding and incorporating humans' complex values and preferences. Recently, language models (LMs) have been used to gather information about the preferences of human users. This preference data can be used to fine-tune or guide other LMs and/or AI systems. However, LMs have been shown to struggle with crucial aspects of preference learning: qu… ▽ More Aligning AI systems to users' interests requires understanding and incorporating humans' complex values and preferences. Recently, language models (LMs) have been used to gather information about the preferences of human users. This preference data can be used to fine-tune or guide other LMs and/or AI systems. However, LMs have been shown to struggle with crucial aspects of preference learning: quantifying uncertainty, modeling human mental states, and asking informative questions. These challenges have been addressed in other areas of machine learning, such as Bayesian Optimal Experimental Design (BOED), which focus on designing informative queries within a well-defined feature space. But these methods, in turn, are difficult to scale and apply to real-world problems where simply identifying the relevant features can be difficult. We introduce OPEN (Optimal Preference Elicitation with Natural language) a framework that uses BOED to guide the choice of informative questions and an LM to extract features and translate abstract BOED queries into natural language questions. By combining the flexibility of LMs with the rigor of BOED, OPEN can optimize the informativity of queries while remaining adaptable to real-world domains. In user studies, we find that OPEN outperforms existing LM- and BOED-based methods for preference elicitation. △ Less

Submitted 8 March, 2024; originally announced March 2024.

Efficiency of negative-illumination photovoltaic energy conversion

Authors: Toru Matsuura, Kazuma Handa, Masakazu Arakawa

Abstract: Infrared diodes generate electricity from thermal radiation emitted from themselves. The negative process of photovoltaic effect has been expected for application to energy harvesting systems converting from terrestrial radiation. However, its energy conversion efficiency has been known to be very low. In this paper, we investigate energy conversion efficiency and external quantum efficiency for t… ▽ More Infrared diodes generate electricity from thermal radiation emitted from themselves. The negative process of photovoltaic effect has been expected for application to energy harvesting systems converting from terrestrial radiation. However, its energy conversion efficiency has been known to be very low. In this paper, we investigate energy conversion efficiency and external quantum efficiency for the negative-illumination photovoltaic effect with a systematic measurement for infrared diodes faced to a sufficiently cold surface. We find that the external quantum efficiency reaches 60\ \% for a diode at a temperature, while the energy conversion efficiency stays below 10^-4 %. We indicate dominant parameters for the efficiencies and propose how to improve energy conversion efficiency. △ Less

Submitted 31 December, 2024; v1 submitted 13 February, 2024; originally announced February 2024.

Comments: 20 pages, 4 figures

Emergence of Abstract State Representations in Embodied Sequence Modeling

Authors: Tian Yun, Zilai Zeng, Kunal Handa, Ashish V. Thapliyal, Bo Pang, Ellie Pavlick, Chen Sun

Abstract: Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promising performance, it remains unclear if embodied sequence modeling leads to the emergence of internal representations that represent the environmental state information. A model that lacks abstract state representations wo… ▽ More Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promising performance, it remains unclear if embodied sequence modeling leads to the emergence of internal representations that represent the environmental state information. A model that lacks abstract state representations would be liable to make decisions based on surface statistics which fail to generalize. We take the BabyAI environment, a grid world in which language-conditioned navigation tasks are performed, and build a sequence modeling Transformer, which takes a language instruction, a sequence of actions, and environmental observations as its inputs. In order to investigate the emergence of abstract state representations, we design a "blindfolded" navigation task, where only the initial environmental layout, the language instruction, and the action sequence to complete the task are available for training. Our probing results show that intermediate environmental layouts can be reasonably reconstructed from the internal activations of a trained model, and that language instructions play a role in the reconstruction accuracy. Our results suggest that many key features of state representations can emerge via embodied sequence modeling, supporting an optimistic outlook for applications of sequence modeling objectives to more complex embodied decision-making domains. △ Less

Submitted 7 November, 2023; v1 submitted 3 November, 2023; originally announced November 2023.

Comments: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023). Project webpage: https://abstract-state-seqmodel.github.io/

"Mistakes Help Us Grow": Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms

Authors: Kunal Handa, Margaret Clapper, Jessica Boyle, Rose E Wang, Diyi Yang, David S Yeager, Dorottya Demszky

Abstract: Teachers' growth mindset supportive language (GMSL)--rhetoric emphasizing that one's skills can be improved over time--has been shown to significantly reduce disparities in academic achievement and enhance students' learning outcomes. Although teachers espouse growth mindset principles, most find it difficult to adopt GMSL in their practice due the lack of effective coaching in this area. We explo… ▽ More Teachers' growth mindset supportive language (GMSL)--rhetoric emphasizing that one's skills can be improved over time--has been shown to significantly reduce disparities in academic achievement and enhance students' learning outcomes. Although teachers espouse growth mindset principles, most find it difficult to adopt GMSL in their practice due the lack of effective coaching in this area. We explore whether large language models (LLMs) can provide automated, personalized coaching to support teachers' use of GMSL. We establish an effective coaching tool to reframe unsupportive utterances to GMSL by developing (i) a parallel dataset containing GMSL-trained teacher reframings of unsupportive statements with an accompanying annotation guide, (ii) a GMSL prompt framework to revise teachers' unsupportive language, and (iii) an evaluation framework grounded in psychological theory for evaluating GMSL with the help of students and teachers. We conduct a large-scale evaluation involving 174 teachers and 1,006 students, finding that both teachers and students perceive GMSL-trained teacher and model reframings as more effective in fostering a growth mindset and promoting challenge-seeking behavior, among other benefits. We also find that model-generated reframings outperform those from the GMSL-trained teachers. These results show promise for harnessing LLMs to provide automated GMSL feedback for teachers and, more broadly, LLMs' potentiality for supporting students' learning in the classroom. Our findings also demonstrate the benefit of large-scale human evaluations when applying LLMs in educational domains. △ Less

Submitted 16 October, 2023; originally announced October 2023.

Comments: In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Task Ambiguity in Humans and Language Models

Authors: Alex Tamkin, Kunal Handa, Avash Shrestha, Noah Goodman

Abstract: Language models have recently achieved strong performance across a wide range of NLP benchmarks. However, unlike benchmarks, real world tasks are often poorly specified, and agents must deduce the user's intended behavior from a combination of context, instructions, and examples. We investigate how both humans and models behave in the face of such task ambiguity by proposing AmbiBench, a new bench… ▽ More Language models have recently achieved strong performance across a wide range of NLP benchmarks. However, unlike benchmarks, real world tasks are often poorly specified, and agents must deduce the user's intended behavior from a combination of context, instructions, and examples. We investigate how both humans and models behave in the face of such task ambiguity by proposing AmbiBench, a new benchmark of six ambiguously-specified classification tasks. We evaluate humans and models on AmbiBench by seeing how well they identify the intended task using 1) instructions with varying degrees of ambiguity, and 2) different numbers of labeled examples. We find that the combination of model scaling (to 175B parameters) and training with human feedback data enables models to approach or exceed the accuracy of human participants across tasks, but that either one alone is not sufficient. In addition, we show how to dramatically improve the accuracy of language models trained without large-scale human feedback training by finetuning on a small number of ambiguous in-context examples, providing a promising direction for teaching models to generalize well in the face of ambiguity. △ Less

Submitted 20 December, 2022; originally announced December 2022.

The coagulation-fragmentation hierarchy with homogeneous rates and underlying stochastic dynamics

Authors: Kenji Handa

Abstract: A hierarchical system of equations is introduced to describe dynamics of `sizes' of infinite clusters which coagulate and fragmentate with homogeneous rates of certain form. We prove that this system of equations is solved weakly by correlation measures for stochastic dynamics of interval partitions evolving according to some split-merge transformations. Regarding those processes, a sufficient con… ▽ More A hierarchical system of equations is introduced to describe dynamics of `sizes' of infinite clusters which coagulate and fragmentate with homogeneous rates of certain form. We prove that this system of equations is solved weakly by correlation measures for stochastic dynamics of interval partitions evolving according to some split-merge transformations. Regarding those processes, a sufficient condition for a distribution to be reversible is given. Also, an asymptotic result for properly rescaled processes is shown to obtain a solution to a nonlinear equation called the coagulation-fragmentation equation. △ Less

Submitted 31 August, 2018; originally announced August 2018.

Comments: 57 pages

MSC Class: 60K35

Measurement and comparison of individual external doses of high-school students living in Japan, France, Poland and Belarus -- the "D-shuttle" project --

Authors: N. Adachi, V. Adamovitch, Y. Adjovi, K. Aida, H. Akamatsu, S. Akiyama, A. Akli, A. Ando, T. Andrault, H. Antonietti, S. Anzai, G. Arkoun, C. Avenoso, D. Ayrault, M. Banasiewicz, M. Banaśkiewicz, L. Bernandini, E. Bernard, E. Berthet, M. Blanchard, D. Boreyko, K. Boros, S. Charron, P. Cornette, K. Czerkas , et al. (208 additional authors not shown)

Abstract: Twelve high schools in Japan (of which six are in Fukushima Prefecture), four in France, eight in Poland and two in Belarus cooperated in the measurement and comparison of individual external doses in 2014. In total 216 high-school students and teachers participated in the study. Each participant wore an electronic personal dosimeter "D-shuttle" for two weeks, and kept a journal of his/her whereab… ▽ More Twelve high schools in Japan (of which six are in Fukushima Prefecture), four in France, eight in Poland and two in Belarus cooperated in the measurement and comparison of individual external doses in 2014. In total 216 high-school students and teachers participated in the study. Each participant wore an electronic personal dosimeter "D-shuttle" for two weeks, and kept a journal of his/her whereabouts and activities. The distributions of annual external doses estimated for each region overlap with each other, demonstrating that the personal external individual doses in locations where residence is currently allowed in Fukushima Prefecture and in Belarus are well within the range of estimated annual doses due to the background radiation level of other regions/countries. △ Less

Submitted 18 November, 2015; v1 submitted 21 June, 2015; originally announced June 2015.

Ergodic properties for α-CIR models and a class of generalized Fleming-Viot processes

Authors: Kenji Handa

Abstract: We discuss a Markov jump process regarded as a variant of the CIR (Cox-Ingersoll-Ross) model and its infinite-dimensional extension. These models belong to a class of measure-valued branching processes with immigration, whose jump mechanisms are governed by certain stable laws. The main result gives a lower spectral gap estimate for the generator. As an application, a certain ergodic property is s… ▽ More We discuss a Markov jump process regarded as a variant of the CIR (Cox-Ingersoll-Ross) model and its infinite-dimensional extension. These models belong to a class of measure-valued branching processes with immigration, whose jump mechanisms are governed by certain stable laws. The main result gives a lower spectral gap estimate for the generator. As an application, a certain ergodic property is shown for the generalized Fleming-Viot process obtained as the time-changed ratio process. △ Less

Submitted 17 July, 2014; v1 submitted 9 July, 2013; originally announced July 2013.

Comments: 30 pages. to appear in Electronic Journal of Probability

MSC Class: 60J75 (Primary) 60G57 (Secondary)

Initial Results from the Nobeyama Molecular Gas Observations of Distant Bright Galaxies

Authors: D. Iono, B. Hatsukade, K. Kohno, R. Kawabe, S. Ikarashi, K. Ichikawa, T. Kodama, K. Motohara, T. Nakajima, K. Nakanishi, K. Ohta, K. Ota, T. Saito, K. Suzuki, K. Tadaki, Y. Tamura, J. Ueda, H. Umehata, K. Yabe, T. Yoshida, S. Yuma, N. Kuno, S. Takano, H. Iwashita, K. Handa , et al. (15 additional authors not shown)

Abstract: We present initial results from the CO survey toward high redshift galaxies using the Nobeyama 45m telescope. Using the new wide bandwidth spectrometer equipped with a two-beam SIS receiver, we have robust new detections of three high redshift (z=1.6-3.4) submillimeter galaxies (SXDF 1100.001, SDP9, and SDP17), one tentative detection (SDSS J160705+533558), and one non-detection (COSMOS-AzTEC1). T… ▽ More We present initial results from the CO survey toward high redshift galaxies using the Nobeyama 45m telescope. Using the new wide bandwidth spectrometer equipped with a two-beam SIS receiver, we have robust new detections of three high redshift (z=1.6-3.4) submillimeter galaxies (SXDF 1100.001, SDP9, and SDP17), one tentative detection (SDSS J160705+533558), and one non-detection (COSMOS-AzTEC1). The galaxies observed during the commissioning phase are sources with known spectroscopic redshifts from previous optical or from wide-band submm spectroscopy. The derived molecular gas mass and line widths from Gaussian fits are ~10^11 Msun and 430-530 km/s, which are consistent with previous CO observations of distant submm galaxies and quasars. The spectrometer that allows a maximum of 32 GHz instantaneous bandwidth will provide new science capabilities at the Nobeyama 45m telescope, allowing us to determine redshifts of bright submm selected galaxies without any prior redshift information. △ Less

Submitted 18 June, 2012; originally announced June 2012.

Comments: 4 pages, 1 figure, PASJ Letter Accepted

Stationary distributions for a class of generalized Fleming-Viot processes

Authors: Kenji Handa

Abstract: We identify stationary distributions of generalized Fleming-Viot processes with jump mechanisms specified by certain beta laws together with a parameter measure. Each of these distributions is obtained from normalized stable random measures after a suitable biased transformation followed by mixing by the law of a Dirichlet random measure with the same parameter measure. The calculations are based… ▽ More We identify stationary distributions of generalized Fleming-Viot processes with jump mechanisms specified by certain beta laws together with a parameter measure. Each of these distributions is obtained from normalized stable random measures after a suitable biased transformation followed by mixing by the law of a Dirichlet random measure with the same parameter measure. The calculations are based primarily on the well-known relationship to measure-valued branching processes with immigration. △ Less

Submitted 27 March, 2014; v1 submitted 1 May, 2012; originally announced May 2012.

Comments: Published in at http://dx.doi.org/10.1214/12-AOP829 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Report number: IMS-AOP-AOP829

Journal ref: Annals of Probability 2014, Vol. 42, No. 3, 1257-1284

The sector constants of continuous state branching processes with immigration

Authors: Kenji Handa

Abstract: Continuous state branching processes with immigration are studied. We are particularly concerned with the associated (non-symmetric) Dirichlet form. After observing that gamma distributions are only reversible distributions for this class of models, we prove that every generalized gamma convolution is a stationary distribution of the process with suitably chosen branching mechanism and with contin… ▽ More Continuous state branching processes with immigration are studied. We are particularly concerned with the associated (non-symmetric) Dirichlet form. After observing that gamma distributions are only reversible distributions for this class of models, we prove that every generalized gamma convolution is a stationary distribution of the process with suitably chosen branching mechanism and with continuous immigration. For such non-reversible processes, the strong sector condition is discussed in terms of a characteristic called the Thorin measure. In addition, some connections with notion from noncommutative probability theory will be pointed out through calculations involving the Stieltjes transform. △ Less

Submitted 28 October, 2011; v1 submitted 5 August, 2011; originally announced August 2011.

Comments: 36 pages, LaTex; The proof of Lemma 2.1 has been removed

MSC Class: 60J75

The two-parameter Poisson--Dirichlet point process

Authors: Kenji Handa

Abstract: The two-parameter Poisson--Dirichlet distribution is a probability distribution on the totality of positive decreasing sequences with sum 1 and hence considered to govern masses of a random discrete distribution. A characterization of the associated point process (that is, the random point process obtained by regarding the masses as points in the positive real line) is given in terms of the corr… ▽ More The two-parameter Poisson--Dirichlet distribution is a probability distribution on the totality of positive decreasing sequences with sum 1 and hence considered to govern masses of a random discrete distribution. A characterization of the associated point process (that is, the random point process obtained by regarding the masses as points in the positive real line) is given in terms of the correlation functions. Using this, we apply the theory of point processes to reveal the mathematical structure of the two-parameter Poisson--Dirichlet distribution. Also, developing the Laplace transform approach due to Pitman and Yor, we are able to extend several results previously known for the one-parameter case. The Markov--Krein identity for the generalized Dirichlet process is discussed from the point of view of functional analysis based on the two-parameter Poisson--Dirichlet distribution. △ Less

Submitted 12 January, 2010; v1 submitted 23 May, 2007; originally announced May 2007.

Comments: Published in at http://dx.doi.org/10.3150/08-BEJ180 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

Report number: IMS-BEJ-BEJ180

Journal ref: Bernoulli 2009, Vol. 15, No. 4, 1082-1116

Efficiency enhancement of organic based Light Emitting Diodes using a scattering layer

Authors: R. F. Oulton, C. S. Adjiman, K. Handa, S. Aramaki

Abstract: This paper presents an investigation of organic LED extraction efficiency enhancement using a low refractive index scattering layer. A scattering model is developed based on rigorous electromagnetic modelling techniques. The model accounts for proportions of scattered guided and radiation modes as well as the efficiencies with which emitted and scattered light are extracted. Constrained optimisa… ▽ More This paper presents an investigation of organic LED extraction efficiency enhancement using a low refractive index scattering layer. A scattering model is developed based on rigorous electromagnetic modelling techniques. The model accounts for proportions of scattered guided and radiation modes as well as the efficiencies with which emitted and scattered light are extracted. Constrained optimisation techniques are implemeneted for a single operation wavelength to maximise the extraction efficiency of a generic OLED device. Calculations show that a 2 fold efficiency enhancement is achievable with a correctly engineered scattering layer. The detailed analysis of the enhancement mechanism highlights ways in which this scheme could be improved. △ Less

Submitted 9 November, 2004; originally announced November 2004.

Comments: 8 Pages, 5 Figures: To be submitted to Journal of Applied Physics

Quasi-invariance and reversibility in the Fleming-Viot process

Authors: Kenji Handa

Abstract: Reversible measures of the Fleming-Viot process are shown to be characterized as quasi-invariant measures with a cocycle given in terms of the mutation operator. As applications, we give certain integral characterization of Poisson-Dirichlet distributions and a proof that the stationary measure of the step-wise mutation model of Ohta-Kimura with periodic boundary condition is nonreversible. Reversible measures of the Fleming-Viot process are shown to be characterized as quasi-invariant measures with a cocycle given in terms of the mutation operator. As applications, we give certain integral characterization of Poisson-Dirichlet distributions and a proof that the stationary measure of the step-wise mutation model of Ohta-Kimura with periodic boundary condition is nonreversible. △ Less

Submitted 18 September, 1999; originally announced September 1999.

Report number: FI-PIA1999-018